{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "![](http://osloyi5le.bkt.clouddn.com/%E6%9C%BA%E5%99%A8%E5%AD%A6%E4%B9%A0%E5%B7%A5%E7%A8%8B%E5%B8%88banner.png)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 医疗费用分析与建模预估"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "_cell_guid": "b1076dfc-b9ad-4769-8c92-a6c4dae69d19",
    "_uuid": "8f2839f25d086af736a60e9eeb907d3b93b6e0e5",
    "scrolled": false
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "      <td>1338.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>39.207025</td>\n",
       "      <td>30.663397</td>\n",
       "      <td>1.094918</td>\n",
       "      <td>13270.422265</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>14.049960</td>\n",
       "      <td>6.098187</td>\n",
       "      <td>1.205493</td>\n",
       "      <td>12110.011237</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>18.000000</td>\n",
       "      <td>15.960000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>1121.873900</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>27.000000</td>\n",
       "      <td>26.296250</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>4740.287150</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>39.000000</td>\n",
       "      <td>30.400000</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>9382.033000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>51.000000</td>\n",
       "      <td>34.693750</td>\n",
       "      <td>2.000000</td>\n",
       "      <td>16639.912515</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>64.000000</td>\n",
       "      <td>53.130000</td>\n",
       "      <td>5.000000</td>\n",
       "      <td>63770.428010</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age          bmi     children       charges\n",
       "count  1338.000000  1338.000000  1338.000000   1338.000000\n",
       "mean     39.207025    30.663397     1.094918  13270.422265\n",
       "std      14.049960     6.098187     1.205493  12110.011237\n",
       "min      18.000000    15.960000     0.000000   1121.873900\n",
       "25%      27.000000    26.296250     0.000000   4740.287150\n",
       "50%      39.000000    30.400000     1.000000   9382.033000\n",
       "75%      51.000000    34.693750     2.000000  16639.912515\n",
       "max      64.000000    53.130000     5.000000  63770.428010"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import warnings\n",
    "warnings.filterwarnings('ignore')\n",
    "import pandas as pd\n",
    "from matplotlib import pyplot as plt\n",
    "import seaborn as sns\n",
    "from sklearn.ensemble import RandomForestRegressor\n",
    "from sklearn.preprocessing import LabelEncoder, StandardScaler\n",
    "from sklearn.model_selection import train_test_split\n",
    "import numpy as np\n",
    "import sklearn.metrics\n",
    "\n",
    "#加载数据\n",
    "df = pd.read_csv('./insurance.csv')\n",
    "#剔除缺失值\n",
    "df = df.dropna()\n",
    "#查看数据分布状况\n",
    "df.describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "_uuid": "dc9600cade1f721de52c0b5be3bf096e7efd75b1"
   },
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>age</th>\n",
       "      <th>bmi</th>\n",
       "      <th>children</th>\n",
       "      <th>charges</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>age</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.109272</td>\n",
       "      <td>0.042469</td>\n",
       "      <td>0.299008</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>bmi</th>\n",
       "      <td>0.109272</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.012759</td>\n",
       "      <td>0.198341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>children</th>\n",
       "      <td>0.042469</td>\n",
       "      <td>0.012759</td>\n",
       "      <td>1.000000</td>\n",
       "      <td>0.067998</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>charges</th>\n",
       "      <td>0.299008</td>\n",
       "      <td>0.198341</td>\n",
       "      <td>0.067998</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "               age       bmi  children   charges\n",
       "age       1.000000  0.109272  0.042469  0.299008\n",
       "bmi       0.109272  1.000000  0.012759  0.198341\n",
       "children  0.042469  0.012759  1.000000  0.067998\n",
       "charges   0.299008  0.198341  0.067998  1.000000"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#查看不同维度之间的相关性\n",
    "df.corr()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "_cell_guid": "79c7e3d0-c299-4dcb-8224-4455121ee9b0",
    "_uuid": "d629ff2d2480ee46fbb7e2d37f6b5fab8052498a"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "数据分布分析：\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#选出特征和标签\n",
    "df['bmi_int'] = df['bmi'].apply(lambda x: int(x))\n",
    "variables = ['sex','smoker','region','age','bmi_int','children']\n",
    "\n",
    "# 数据分布分析\n",
    "print('数据分布分析：')\n",
    "for v in variables:\n",
    "    df = df.sort_values(by=[v])\n",
    "    df[v].value_counts().plot(kind = 'bar')\n",
    "    plt.title(v)\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "_cell_guid": "98eb1d06-25c7-4fcd-a237-6b8430d006e5",
    "_uuid": "6809020e5490a674d3c1e7ed88ca1d56aec2413c",
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "平均医疗开销分析：\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": 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VW5IsTbIiyYqRkZEeWpckbUkv4TAZOBy4oKoOA/6TP04hAVBVBVQPz/EEVXVhVQ1V1dC0adPG62ElSZvoJRyGgeGq+m6zfjmdsPh1M11E8/2+ZvsaYP+u/Wc0tc3VJUl9MuZwqKpfAauTvKApLQBuB64ENl5xtAS4olm+Eji5uWppPvBgM/10NbAwyd7NieiFTU2S1CeTe9z/74HPJXkS8FPgrXQC57IkpwD3AG9sxl4FvApYBTzcjKWq1iY5G7i5GffBqlrbY1+SpB70FA5VdRswNMqmBaOMLeDUzTzOxcDFvfQiSRo/3iEtSWoxHCRJLYaDJKnFcJAktRgOkqQWw0GS1GI4SJJaDAdJUovhIElqMRwkSS2GgySpxXCQJLUYDpKkFsNBktRiOEiSWgwHSVKL4SBJajEcJEkthoMkqcVwkCS1GA6SpJaewyHJpCTfS/LVZn1Wku8mWZXkC0me1NSf3KyvarbP7HqM9zX1u5Ic3WtPkqTejMeRw2nAHV3rHwY+UlXPA9YBpzT1U4B1Tf0jzTiSzAFOBA4EFgGfTDJpHPqSJI1RT+GQZAbwauDfmvUARwGXN0OWAcc1y4ubdZrtC5rxi4FLq+p3VfUzYBUwr5e+JEm96fXI4aPAe4DHmvV9gd9U1YZmfRiY3ixPB1YDNNsfbMY/Xh9lnydIsjTJiiQrRkZGemxdkrQ5Yw6HJK8B7quqW8axny2qqguraqiqhqZNm7ajnlaSBs7kHvY9Ejg2yauAqcDTgY8BeyWZ3BwdzADWNOPXAPsDw0kmA3sCD3TVN+reR5LUB2M+cqiq91XVjKqaSeeE8rVVdRJwHXB8M2wJcEWzfGWzTrP92qqqpn5iczXTLGA2cNNY+5Ik9a6XI4fNeS9waZJzgO8BFzX1i4DPJFkFrKUTKFTVyiSXAbcDG4BTq+oPf4K+JEnbaFzCoar+A/iPZvmnjHK1UVU9Apywmf3PBc4dj14kSb3zDmlJUovhIElqMRwkSS2GgySpxXCQJLUYDpKkFsNBktRiOEiSWgwHSVKL4SBJajEcJEkthoMkqcVwkCS1GA6SpBbDQZLUYjhIkloMB0lSi+EgSWoxHCRJLYaDJKllzOGQZP8k1yW5PcnKJKc19X2SLE9yd/N976aeJOcnWZXkB0kO73qsJc34u5Ms6f1lSZJ60cuRwwbg3VU1B5gPnJpkDnAGcE1VzQauadYBjgFmN19LgQugEybAWcCLgXnAWRsDRZLUH2MOh6q6t6pubZZ/C9wBTAcWA8uaYcuA45rlxcAl1XEjsFeSZwFHA8uram1VrQOWA4vG2pckqXfjcs4hyUzgMOC7wDOr6t5m06+AZzbL04HVXbsNN7XN1SVJfdJzOCR5GvAl4B+q6qHubVVVQPX6HF3PtTTJiiQrRkZGxuthJUmb6CkckkyhEwyfq6ovN+VfN9NFNN/va+prgP27dp/R1DZXb6mqC6tqqKqGpk2b1kvrkqQt6OVqpQAXAXdU1b92bboS2HjF0RLgiq76yc1VS/OBB5vpp6uBhUn2bk5EL2xqkqQ+mdzDvkcCbwZ+mOS2pnYm8CHgsiSnAPcAb2y2XQW8ClgFPAy8FaCq1iY5G7i5GffBqlrbQ1+SpB6NORyq6ltANrN5wSjjCzh1M491MXDxWHuRJI0v75CWJLUYDpKkFsNBktRiOEiSWgwHSVKL4SBJajEcJEkthoMkqcVwkCS1GA6SpBbDQZLUYjhIkloMB0lSi+EgSWoxHCRJLYaDJKnFcJAktRgOkqQWw0GS1GI4SJJaDAdJUsuECYcki5LclWRVkjP63Y8kDbIJEQ5JJgGfAI4B5gBvSjKnv11J0uCaEOEAzANWVdVPq+r3wKXA4j73JEkDa3K/G2hMB1Z3rQ8DL950UJKlwNJmdX2Su3ZAb4NgP+D+fjexNflwvztQn/jvc3w9Z1sGTZRw2CZVdSFwYb/72NUkWVFVQ/3uQxqN/z77Y6JMK60B9u9an9HUJEl9MFHC4WZgdpJZSZ4EnAhc2eeeJGlgTYhpparakOQdwNXAJODiqlrZ57YGiVN1msj899kHqap+9yBJmmAmyrSSJGkCMRwkSS2GgySpxXCQJLUYDpImpCRPSfKCfvcxqAyHAZXk+UmuSfKjZv3gJP/Y774kgCSvBW4DvtGsH5rEe592IMNhcP1P4H3AowBV9QM6Nx9KE8EH6Lwh528Aquo2YFY/Gxo0hsPgempV3bRJbUNfOpHaHq2qBzepeVPWDjQh7pBWX9yf5C9ofuGSHA/c29+WpMetTPLXwKQks4F3At/pc08DxTukB1SS59J5W4KXAuuAnwF/U1U/72dfEkCSpwLvBxYCofPWOmdX1SN9bWyAGA4DLsnuwG5V9dt+9yJp4jAcBkyS07e0var+dUf1Im0qyf9mC+cWqurYHdjOQPOcw+DZo98NSFtwXr8bUIdHDpKkFo8cBlSSqcApwIHA1I31qnpb35qSGs0VSv8EzOGJ/z6f27emBoz3OQyuzwB/BhwNXE/no1k9Ka2J4t+BC+jce/NfgEuAz/a1owHjtNKASvK9qjosyQ+q6uAkU4D/W1Xz+92blOSWqnpRkh9W1UHdtX73NiicVhpcjzbff5NkLvAr4Bl97Efq9rskuwF3Nx8hvAZ4Wp97GihOKw2uC5PsDfw34ErgduCf+9uS9LjTgKfSuTP6RcDfACf3taMB47SSpAknyRCdO6SfA0xpylVVB/evq8FiOAyoJHvR+UtsJl3Ti1X1zn71JG2U5C7gvwI/BB7bWK+qe/rW1IDxnMPgugq4kU1++aQJYqSq/PyGPvLIYUAlubWqDu93H9JokiwA3gRcA/xuY72qvty3pgaM4TCgkrwLWA98lSf+8q3tW1NSI8lngQOAlfzxyLa8SXPHMRwGVJJTgXPpfNLWxn8E5R2omgiS3FVVfn50H3nOYXC9G3heVd3f70akUXwnyZyqur3fjQwqw2FwrQIe7ncT0mbMB25L8jM6057BS1l3KMNhcP0nnV++63jiOQcvZdVEsKjfDQw6w2Fw/a/mS5pwvJ+h/zwhPcCSPAV4dlXd1e9eJE0svrfSgEryWuA24BvN+qFJvOlIEmA4DLIPAPPoXMpKVd0GeBmrJMBwGGSPVtWDm9R8Gw1JgCekB9nKJH8NTGo+kvGdwHf63JOkCcIjhwGT5DPN4k/ofH7074DPAw8B/9CvviRNLF6tNGCS3A78JfB1Op/N+wS+t5IkcFppEH2KzjtdPhdY0VUPnfdY8qS0JI8cBlWSC6rqb/vdh6SJyXCQJLV4QlqS1GI4SJJaDAdJUovhIElqMRyk7ZRk9yRfS/L9JD9K8ldJXpTk+iS3JLk6ybOSTE5yc5JXNvv9U5Jz+9y+tE28z0HafouAX1bVqwGS7EnnpsLFVTWS5K+Ac6vqbUneAlye5O+b/V7cr6al7WE4SNvvh8B/T/Jh4KvAOmAusDwJwCTgXoCqWtm8ZclXgZdU1e/707K0fQwHaTtV1Y+THA68CjgHuBZYWVUv2cwuB9F5a/Rn7KAWpZ55zkHaTkn+HHi4qj4L/AudqaJpSV7SbJ+S5MBm+fXAPsDLgY8n2atPbUvbxTukpe2U5Gg6ofAY8Cjwt8AG4HxgTzpH5B8FvkLnbdAXVNXqJO8EXlRVS/rSuLQdDAdJUovTSpKkFsNBktRiOEiSWgwHSVKL4SBJajEcJEkthoMkqeX/A1RXNe7Cf924AAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/usr/local/lib/python3.6/site-packages/pandas/plotting/_core.py:1716: UserWarning: Pandas doesn't allow columns to be created via a new attribute name - see https://pandas.pydata.org/pandas-docs/stable/indexing.html#attribute-access\n",
      "  series.name = label\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#平均医疗开销分析\n",
    "print('平均医疗开销分析：')\n",
    "for v in variables:\n",
    "    group_df = df.groupby(pd.Grouper(key=v)).mean()\n",
    "    group_df = group_df.sort_index()\n",
    "    group_df.plot(y = ['charges'],kind = 'bar')\n",
    "    plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "_cell_guid": "078f27b3-a846-47c8-a7d8-5412d44b3fbd",
    "_uuid": "109f80eba0b4c3fc6f6479a805b94fed55dbf3cb"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "两两变量分析：\n"
     ]
    },
    {
     "data": {
      "image/png": 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flKK7/u1YmztdTpS1nL4v1HbMd89//u4jnE7IWLljP+Lffxl/veFdJGUNY4fEctuWNMexpUA3IrQEMnsJIXEAPwfwPoApABoALAdwnFI6KLMPAXDG/O6F6dOn0927dxd5xAwljh7/mXuhdpqQVCzeuNshszVjbCU23DkdZZmVM9NRLdu611Vqbu38OLb9/ihmTx6O2vqDVltzpozAihsnYFRlFK0JCUGBR3lYcKwiJyQVbx9uwc6DzfjHv7wcHWkVl1ZEcaxNRHlYgE4pdB24d3uj1W7t1y7HLVeORJA3+HnZsncV0SBUneLJt4+g5tKBuHzEQCy3yTKtXRBHZSwIUdbw1uEWLP3VXrz94PWggKOtVXNrUPfyIQCwzsNc4QCQ95oUS9bpAtDjA/GyVUlWcS6tOmSq1s6PY2BYQCjoj5ScqKhIpDXLtsrCPKIBwZekO03T0SGpOCsqVvuDogGUhwRfyrh3pBU0nerAuKHlVkLihy0dqB5WfsFyifZnuxfZbo/a6sV+94uSakyMYVCAfvnWEcyddgkGRoKIhng0n0tjYCSAcAErq9mrsRGBQ5uoWH7q3i9n/JhkrPa2iU7JuifumAoCozx406kEdh44iflXj8KQWK48npvtrF0QR2U0WJDdm++e2jmTHO8NwHgHPXHHNNyz2SlVOiAsIBwUCnpvXQQUZKelMnmeDuB/AFxDKX2XELIWQDuA79ony4SQM5TSHN4zIeRuAHcDwKhRo6Z98sknF2nkDCWKHnHyftqpTikmPPIiVNsvdoEj+OCHNzuktjyVJSQNAMXphIxRlVGrLXMV+sFn9ntqO9ftPITmdglr58dREQ2iLSU7J7mZ7RxHMOFRo93ar12Or14xHMu3NWLL316N+55qxNKZ1VY4fv2uJvzktjgW/uJdrF0QR0UkiITcObFJSCo2vn0E615vsvp44b2TuGPGaKut8VVlONxsZJkDcOhP2ycXAEpJbaPX2qqm60jJGnQKa3LIESAS5MFfqC5Xpv3PzklYuWOfdQ/r5k3Bnw0M+dK+qdGb/QOtIhKEIPjUvijn/LioiPrTfi8Mf1/0znvq3a/rFGKmGElCUlEZC6ItKUPS9Kwf48b9zjcp9fohVBENQDKTEu0T5YVTARgryFUDw0jLxgq43Y4fn28sNAge/WqajqSsOSbbC67+XEE/vsx3z6F/uRkTH3V5B/3LzTh8KoHqYWVIpFX894ctmD66ApWxEEBQ0HuryCioo5KgbQD4FMCnlNJ3M9+fBjAVQDMhZDgAZP4/5XYwpfTnlNLplNLpQ4cOvSgDZmA4X/hpp4WG3jiOoCwkgCME0aCAsrBgVZ9avKkBM+t2OSgd+ZIBs0tyL9/WaOmcupXBtits3HLlSCs5q+lUwjUc33QqYRy/1Th+6ZY9mFm3C02nErhncwPWvHo4p8y4vS1TkL9+3wnXRMLOEuLu16QsJPT05KPXoBBbFWUNizc1oOZ7L2PsQy+g5nsvY/GmBt+oA6KsYeWOfY57uHLHPt/ad7XdrYZN+9a+S0KiX+3b7bi/2m5PvfvNZEE1k3QqKgatLTcBubHLZDmvBL6UqkOnyNF2PiMquGfLHsz419cx9qEXcOxMKseO793WiFSeflOqjiWbGyz/u+bVwwUn9pnvHi/a2+FTCcu337OlAWOHllvXoZToRiUxeaaUfgbgGCFkYmbTDTAoHPUA7sxsuxPAb3pgeAwMvQ5eRU7yZXTrOkVCUqFT6kgasWeH25PovBLqzCTD7CQ/+z5lYQGxEI+6eVMwY2wlBkQCrv2ZY181t8ZaMTaPt5fzrp0zCXOmjHD0MSASwLihMaxfOBW7Vs7EuKExS/3hYiUD2q9pQlJ7JXevWCh1nedSb5+h5xAJcBgQCVgJy7GQ4Jm019X99krgiwQ4179l9+Pl6/L1eyFJg+a7Z+eBkzl+/PH5cYwbGsPOe6/DnCkjrPeF2XZ33ls9hVJ6Sr8L4FcZpY2PAHwLxuT/KULIXQA+AXBbD46PgaHXgOMIKmNBbLhzekFh2+zQ4O8euN4qI2tmRj926xVIZVYGzBVit/LFTacS1mevMtgdaRU8AUIBgsduvcKxn72/UZVRHG0VUffyIWu72W42ZcQs+1q/7wSuGl2B9pSC2vqDeOCmz+OhZ9/DHz5uw7JZ1fjZHdMc52EflyhpVjGXC0Uv5Z1eNBS7BDprn6E3QlV1JGTVeMYpsGxWNZKSitaE3K37Lbr4qmWzqtGalCFKuX8zkwPNbV5+WpQ1Tx6xW59dHWPCfPf8zZfGIhLoLESVSKt40katWzW3BtVDY9b4zLbP573VkyiJlWcAoJQ2ZsIvNZTSWyilZyilrZTSGyil4ymlX6aUtnXdEgND/8D5hG2zQ4O6Tc9Z4AhaOiQIPAFv04a2azvbNTzX72qyNH3PJCVXrV9V05CUNHz3142YWbcLzzR86tivpUNCNMhDVjQIfKZ/Wx+qnlva+MFn9uPb11dbfTy/9ziWzqy29FVVnWLNq4exZHMDOAL30ss+esT+rrVbbB1me7n27DLufqDY448IvOv4I0LvW2VjKBwpVcNZUcHbh1sgcATfvGYMmk51YFA0V/N4bQH6zm6rsd+8ZgyWb23Emlc+yFndHRwNYJ2tBLhd977Q1dwLXQE23z08ZxSiEmUNS7KodQ8+sx93fnFMTonuUqEblUTCoJ9gahsMBaDHn1Y/7NQrYchtOwiwYntnkl5K1rD7k1bELx2co0G7+Z2P8fX4SAyIBCBKmlV6W8yobYSDPNKyBo1Sq/S1pcKRVeLYnhxiqm1k93cmKUHgeJRHBHSkVKi6hsGxkGdiSVJS0fBJG4YPjDqSBOv3ncCT35yOqZ+rQFlYQErWkFI0DI4G8dm5FHQKjBxs6K5ynKGDfSErH4UmbV4geq2t6pQ6bMV+T/04f51SyIoGRe+0swBHEAzwvrX/5genMHVURU55br/un6rqSKmaNf6IwPuSLAiwhMFsXKx3v04pKAV+d/gUrhpdiXCAw2fn0hgSC4ICDnvt6n47Erplw9dGQ0ZZ70effw/PN57IKcUtcIBOjX9m8nckwCGl6udlC+drP/n2z+cL04qGsNDjtmlHQQMpJdoGAwNDgciXoW1KHNm3l4d4Bw1i2axqzP/CKCzdssehpCErndq09u1BnuBsSsH9O7xVOB55zlDhWD2vBi0dEniOOEKDtb99HzsPNqN2ziTMfvxNzBhbiS9fVpWRmmt00DPSSsozBMpzBNXDynMoHUuuG4Oh5WEsyZJJ+tPJcygPBx3KG3bVkO5SLS4k9NkXYNcxtl/XtKz5IiWnKhraXaTwBgEI+iCFZy/PbW9fVjSEfWgfAASBQ3lm8uQnVaO/U4Z6CqqqQ1Q0CBzB5cMH4s0PTmHGuCGgAH725ke45cpLXBV+3O5JV1Kiq+fVQKcGTa1+3wnMGFuJn90xDaeTSo6iRzQYsnxOob7HXAEu5Jiu7M3LFx5tFRELCQiXYLSlZGgbDAwMhSMfZcBtu5JFg5g9eXiOEsD9O/bn7Oe2vSsVjvt37Ies6ogE+Ly0j1VzjZeDGz1Dp7m0CzPkrevux4yqjLmqG4yqjLmW8DbH212qRSklvxQDGnW3Fc2naKe9XHt2GXc/UOzy3MVEf6cM9RRSqhHN0qhhOzPGDcFZ0ZjMzp483FPhxw32e+jlU1fcOMFBAUkp3VP0uFB0ZW9uvnDVXKNMd6naZd9f/mBg6IfIzpa2l9fuqvQ1kD9D22v7+oVT8fze4wWpcIwYFAEhwNO28sSpTFhyze1xiLIGXTfoILVzJlm0C/P4kYMjkJXOcuBJSQVPCDieACpQNSB0XmPvarzdUeE436TNvoaLoVZx0+SqnPLWpaSGoWnGSqVpw9EA70sBlmiQd5SDNrXSWXnu4iIWEhDJPONVA0IoDwsI8pxVntrNl3ndE7sP9/KpoyqjFvVB1w1Kx/n04RfMsWZT78KZqIrlCxdNRyTIo+lUwkoCFzhSknbJJs8MDH0Q9jCZvbBJ7ZxJnnSHQjK0vRQCTA3ltfPjON0hdanC0XQqgUsGR6ywvj0s6RaizFbSOHk2lVM5cPW8GtTZqCFmSLOrsXttt4+3u1SL8wl99jUUW01CVjTcPHm4gxbiJ62i2OPXNB2tydwiKZWxwiq55UNa0VzD/GlFQ9QnyglDLsyCJGVBAd/7+iR0pFUkJDWvL/PyLXYffuKsO01NlAyOcVLSHJSJQvvwC6Ks4d8XxDHtcxU5z6Npzxxn1A9Y+It3+wSVjdE2GBj6IOxhMntBEDcN5XULrkSAcyoLuGVor50fz9nPrsFshrVjofx0jLXz49h54KQjxGgPS7qFKO1KGl50jmxqiD2kuWpuDY62Jl3PiSPIuSb28fYnqoWfKLZaRbFpFQEPNY+AT5EDUXEvkuJHCNuNunT/jv3QdR8GzuAJjVIs39poJQ2alA0vX5bPt9h9eD51IDfKhLOPrhU9LhTRAI9rxw/t0p77EpWttKb6DAwMBSGbMmCG/MyV2No5kzC+qswqPx0M8KAUqJtXgz8bGEHTqQRePHDSCjeameEcT/DaH5sdofLn9x53hggzKwiPz49jaHnIUuFYc3vcaudb145BzBZiLKT4ilkMpe7lQ/i32+Oe++y89zqs39VkhTQPN3eGCP/ru9c4qB5HW5OoLBuIupcPWNfEVNsw6SP9iWrhJ8JBHq81NOfQKu6YMdqX9otNqwgGeKQ70g57OZOUMKQ81PXBBSAWElypFX6MPxryKHIRKr1JSinBpBJFQwIopY7iTyZMP7VhkeGbvXwLxxEMjgQs+1uxvRG1cyZZtlK38xDW3B632szXBwAkJDUvfay76izmcYU8j32JysZWnhkY+ihMykB2ydP6fSdQW38QacXQWl68aTcmPPIiHnh6PzQd+PvtjZj9+Jt46UAzQACOEJSHAxAEzqGgMOGRF7F0yx7M+nyVVd3vqtEVSKRVLN7UAEXTkZJViLKGuzYaffzyrSNoE2XcvakBEx55EbX1B7HyKxMtqgcAK0RphxkuN8tre5Z+zdBHVs6eiI6UYhVKqd9nSDqVh4NW33dvasDAjEydeU1E2SiSEg32fp3R3g43W7nhsiqkfSq1a9Iq7DDtxA8oioZwQHDYSzggQPEpuSktG9SK2vqDmPjoi5bd+nF9SqnMcV+BpukWlSgpqWhNyjjaKrreh6OtouFb8/gWTdMtX3m4OYHmdskqaz378TfR3C5BlPOXtDYLPrUmZSzO+ODFG3ejNSk7qp2aahn59nGD/bj2lOI6jkTaWVm1VHScuwKbPDMw9HF4hcp0HV2E+3LDabqLgoL9GCOUSDrDxBSOUJ6biseDz+x3UD28QpR2GoBbgRY7feT+HfvBcQTP7z1uhd7t9BVHKJuipMOHvRVutmJcb39oFcWmhcgetBDZJ1pIMdVI+lJ4vFQgZjTHl29rBKXwLGLyk9umYFA00OW9sNN6vOh20UDXJa0LUV7prjqL/bjn9x7H2gXxHJ/85NtHSlJNoysw2gYDQx+HV6gMBK5qBeOryrDhzumICFxnGC9DvYh6hJotSkUmlPj2g9dDp7mh9ephZY7jT5xNgSNANCTgjKigbl4Nhg+KeIYoQzKHJ+6YhvKwgI60inUL4qgsCzmoGUBnuLD2t+9jdGUUP7tjGsrC7mMfOThiXJvzDB86wpw+FVbpS4h6hHH90HgGLg4tpFi0CrP9YtFO+lJ4vFQQy1A11i2Ioyxs3FurAFTGl6VkDedSMsrDXa+42u0jm24nyprln8MCh3CAw68WXw1RMoqkqDoAYlA1IgHO/Tm0KVxkqzO57eOGSIBz+OmKSBB182owMBJENMTj+JkUPjqddLTTE8V7itEnmzwzMPQDuKk+pGXVU60gGuBzRO9Xz6tBROFcs/hPnk1ZhU1MJYwHns5V9/jsXMr1+BXbG9HcLmHV3BocP5OyQpQmZoytxPEzKRACLNva6Dg2LWuorT+Yk8GdSKuYM2UExg4tx5LNDaibV+OpQHC+md5uRQH8KKzSl1BstYpiF2ExaRU59uJT+6LH9RElFWU+XJ/+rPRysaHrFIqqIaXqUDSKRLrz3mYXMZFUDSlFR1kof+A/+/mp33cCLR2SwYEOCmgoVWz1AAAgAElEQVRNytj9cSumfa4iR7Fl2++PYt3rTcb3BXEsm1WNNa8ettrOVrjoTkEn0wfW1h+0+v4/C6eCEILFm3a7qrz0RPGeYvXJynMzMOSix2c8xbRT81c4pRR3b2pwOMwZYyuxYdF0ULj/7YmF03DPFrdjpkHVKQiA9rSKA8fPYsa4IRgQCSCRVvF2Uwu+u7URv3vgeqx4al/O8faqgnXzanJk6FbNrQHPASszYW638b512OjjqtEVWL9wKnQKDIoGcLRVxJpXPsD9syfigafdjp8GEHJeqxEJScXijbvznseGO6dfjElLr7VVUVIhqTrOpRRcWhHFsTYRAyMBhATOl8lnR1pxtdGfL5rmy+Q8kVbwn28dwezJw62VtZ0HTuJvrh3jy+RWlFScTSm476l9lp3/5LYpGBQJ+LY638vQZ8tzJyQVlFK0JmQ89Ox72LBoKkRFx/Ktzsqoz+/91EiWDna98mxWKywLCWhPK1b+SjTAI6Uak1FRVl2fAdMPmd9/dsc0R6XM7MljdyaYbj5w18qZeOjZ9xzbVnx5vJUgnpRU/PKtI46JfLF9pZevztMnK8/NwMDghN1J/mrx1a6hukgmxOb2t/KIe6g5EhSw8BfvYu38OIYPCCMk5Op9/ukHN4HjSJcFSYYPiqClQ7KoFiYlw0thIxLkrb7/9P2b0CrKkLXcF9fwgeG8Yz+f1QivMOeFFlbpSwjyHBKyioeefa/TDhbEUc73ftoDAESCfE455VVza6zn40IRCnAISASP3XqF9eMiwBGEAiwVqdQQ5jlwPEE0KGDV3MkQZR0VsaCTevbyIbzw3kl854bx4Lrg5es6xZmUkqPdfPDEWWuluWpACGs8fKLph8zvsZCAx269AqMqo5Y2tN3PdYfm4+YDL62I5hTnuuXKS3D3pgbHeTS1JC9aEZfuUlK6AntKGRj6EewJHmZo0Q6zOIiXmoVXRnXTqYSVUJVSPfRrZQ2Hm93btRckOdycwNU/eg1LNjc41DI60l33nZBVnBUVLN+am5SY8FBnMI8/nzKxXhnu2YVV+jNSqpZzH5ZvNezDDxRbbUOUtZwE0wef2e/bfRVlDcu2NWJm3S6Me/gFzKzbhWWZ54ShtJBSNSQlFcfaRAyOhbB8WyM+bEmitv6gpY5hFiwpxD69tJtnjBti+dalM6s91TxMP2T/PrNuF/56w7ueKh/nq4Lh5gOPtTnH45akbSaY28dXTJsvlvIMmzwzMPRR6DpFQlKh08z/OnX8Co8G+JwiEKZihVt299r5cZQFBdfCEeOGxrDz3utQNSDkuSJYFhZci684CqgsiKN6WAyN/3QjbppchfKwUfZ718qZKA8LeNxjvGYfAyIBjK9y14kuDwdy1Bkezxp79mqE2zU0r90TmXF9+KOvYtfKmVi/cCrGDY1h18qZeGLh1H6vbFD0lWEh137Xzo8jIvhz3S9GefFil/8uJryejf4Isyz3kLKgdV9/+kYT1s2P5/iIQuzTa7XU1I2eM2UExleV4fFXc9U8zCJUXj4yO3mvu/fQTeUjFuRRN2+Ktc1Ls796WJnvKjD5fHUxlGdK4yllYGA4L3hx2CIB3koM+fB0Eh+1dFhqBUdbRYdiRfXQGNYvnIrycAAJScXGt49g3etNWDar2lC8CAnosG03k0PyJYrdftUoRIO8FapOSipSioY1t8eRSKt40tbW2vlGURVR1qzQ/7JZ1Xhi4TSUR4Sc8Zor42dFxbX/lKyCAFhz2xRUDQyjI507dnv54nw8QACQNd1BSfjJbVNQW38wkzAYv0h3uvei2AmDqq4jGuQdahsCR6DqOgQf1oWKPf5it19M9ETiV2+FpumQNR2SqoNSZ0RE1qjDR6xbEC/o+ngl8LWnFCybVY0FXxiFRFpFc7uEupcPWfSQY20iAgKHO68Zg+/cMN7VR5pJgBd6D7OpHkdbRfzgv/4IoFNdRJQ9kmJlFR/88GbflC+6OpdiKM+wlWcGhj4IL91OjoP1K3z9riZccckgLN2yByu2N0LgCVo6JOvX+fwvjMKm//4YTacSuGdzA9a8ehiqTrHm1cO4Z3MD2tOKY7upUwvAdUXw2T2fIhTgsHhTA2bW7ULTqQSWbG7A1T96DR0pFUuy2lq+rREAwX2ZBEOr7y0NOJOUEA3yjvGunR/H83uPY80rH7jq/wJGwqHAcxAl1XXs9vLF+bRPjb85KQn3PbXPKg++bKs/ZZZLGcUub63oFIs3NSD+/Vcw9qEXEP/+K0ZxHp9WQIutIx30uD7BEph8dlcXuC9CVDTIGsVZUcG5lGLZzYobJ2Dljn1Z16gwv+C2Wrpqbg3e+fA0vnnNGCRlDSlFw+p5NWjpkPAX636Hhb94Fxwh+OffHMQ9mxvQfC6d4yPPV/+5K1iKLhlZ0pYOCS+8dxK19QfRlpSN6KaL9vMv3zpiTeL9+LHV1bkUozALW3lmYOiD8Ar7hQM8QjxnlXyVFc36nJa1nFLEi744GgMiAVe9W6/Ss7GQAFnVrBXipKQiwBFLf9etDHd2IuKcKSPw7eurURbuLOFtTzAZHAshkVaspMKEpILqFHfMGI0Z4xJ47Y/N2LBoOiJB3qET/fNF0xDkCAIB3rW/aIg3ytgG+C4TTVjCYH4EAzzeP9LaeY/SKvYcbcN1E4b50n6xaQ/hII+65w55lkS+UAQCPFpaEjnl4oeUD/Sl/WLq6RYrCasUEQ3yIITYlBsoYiEBAz38YyHXKHu1NCmpiAR4DIgMQVlYsGz8vqcanX4us8oscATDBoRBKTVKdIdybcDPe2gfbyTAQZQ1y6YrIkErOpRIG7519uThiPiYGNsT9shWnhkY+iBEySNJQlLRJhoSXyu2N+J0srNU9l0bd+NcSsGK7Y345VtHEA4IWLplD0SPMsKi5J6wdbg5ge/8uhEdkoK0oqE8HEA4U+7aHtK0JyXaExHnTBmBlV8x+rOX8M4uAd6eNlarV2xvRHtKwT1b9ljju+GyKpxLyY5Stu0p47zPpVW02MqBZ/dnlqb1vIZ5SuKyhMFOpGUN1cMMje0Jj7yIJZsbUD2svGTKcycl1bUksl/tp2UNA6O55eL9uD7dLbdcKFj5bwOapkNVdSTSRrLg6YSEjrSa+SHknsxX6DWyr5bGggLaRBlLt+zBybMpJDLJic3tEo6fTWHhL961khLNfo61ifj0TMpIEHRZcfX7HnIcQUTg0JrofKf88q0j1rhNH3DiXBo7D5wseXssmckzIeRjQsh7hJBGQsjuzLYKQsgrhJDDmf8H9/Q4GRh6AzjOvcQ1R4gV3lo6s9q1PPDSmdWOMtq67l5GOClrXZbIttMgAGco315i+zeN+ctoZ5cA5zlijcnrPDhCcigdJh0kFuStRBu3/rIpLoWUxLUnPrJSyMUtPw0UnxZSbNpGMa9PsWkVrPy3AVHRIOsUKUVDWZhHJMDjrKjg/h37XUtzd/caiUqnco1OgY1vH0EsyGP1vBrsPHAyp5/V82pQFuYxOE8Z8GLcQ3tJcVWnjveI3ZfPnjwcy32ktvWEPZYabeN6Sulp2/d/APAapfRfCSH/kPn+YM8MjYGh9yAc4FG30z3k7EabMGGnHphUDbPUbPZ+Q8tDECXNCst3pFXIqoZ/uz2Of/7aZRA4HtEQj460gmiAB89zCLqEqn9xpxF2VGwUkkJKgHd1HlUDw/jghzejPaXg+b3HUfvb962/RUMCHn7ugFXu1oviEuQ4x1gjQmfYsyIacPwtwBGsuT3OSiFnEAsJWPK/xuTQNvyiVRSbFhIO8tATeg6VKexTKLiYtJNokHd9hvwKY7Py3wbMexUNCvjd4VO4bsIwy38tnVmNEYPCVtJ1Ss7VV/ZCNuXGXmJ7xKAI1r3ehKaWJB68aSL+5tqxiAQ7/ZQoqYaONAHCGX/lReG5kHuo6xRpVYOuA5FgJ1XDbtP53jF+0ip6wh5LZuXZA18HsDHzeSOAW3pwLAwMvQairHmGnN1oEyZM6oFZRru2/qCnNvPh5gQWb9qN9rSCze98jI60gmVbG7Hlfz6GpgP3bOkMR7cmZSMrXdEwtDzsCFWfEWW8+cEpnEsb1bJOnk250kTMEuDN7ZJDs9nrPJKSivaUgqVb9lgTZ/Nv7SkF9ftOoLb+oGf436C4yI6xtonGeeg6tegv5t86JA2g8C0hpdShKBouHz7QQdu4fPhAKD6tNhWbFqIqGsIBwXGPwwEBqk/j96I9iT7QQtKKO9Uq7WNCXzGSsEoNsmLoO7enFcQvHYyEpOJ0QrKu/ef/8SWDanEuBc5DXzkbXpSbZbMMbWTT39XvO4FVLx1CW1LGwl/8Hld+/xX89YZ3IcqaUcUzU8UwH4Wnu/dQ1yk60grakjL+862PcPxMGndvash5V+R7x/hNq7jY9lhKk2cK4GVCSAMh5O7MtipK6cnM588AVPXM0BgYehfyhbHsahtuYen1u5rAkU5ahJvmczY94+vxkdb+X4+PdC+SomhQdJrzt/t37MfUURWdNBEK13C2TmGNkerUlf5hPw9dpw46iD20/5vG467XxH6tOEI8z4OpDXQN2eVeL9/WCNknnqPuQXvQfaKFSB7jl3waP+dBC+mq+lwh0HWPZ0jv+liGwqHo1KKHnRUVcAAiAf6C6DhuvmX51kZ885oxlr/LR3EzfVS+9i7UV4mKhjMZesrsycOtMWS/K9x0/VfNNagmpU7zKSXaxrWU0uOEkGEAXiGE/Mn+R0opJYS4Wmdmsn03AIwaNar4I2Vg6Ab8tNN8YSz7drvahp16AMAR9v3sXAo//kYNRg6OWOWy7eoXduWNfCoc5mcTdlWNH3+jBhwBhg+KuB4/cnDEQdsIZY3dpH+0pxT8pvE47pgxGnfMGO16jnfMGI150y+FrgOEI4gEOPzHndMRzmS2RwM8iEcpcbfzML/3F7WBQmy12GoYUY/2oyVSxKSYah7RkAdtI+SffRZTzcMvFPvdHwsJoJSCEKM0NyHGdamdMwnjhsaQyGh2N51KFOwbvJQjysKCpWahqJ10Ijc1IruN+qlEYb/nZiluOzXDHINJhzOpbnbVkGiQx998aWyvtJfzQcmsPFNKj2f+PwXgOQBfANBMCBkOAJn/T3kc+3NK6XRK6fShQ4derCEzMJwX/LZTrzCWXZuzQ9IcYenTSRkrtjfibFJ2hH1X7tgPQoxQuVku28RVoyvQYSv13ZFyD0d3pNW8qhoPPL0fFMDJsylPmohJ22hNSA6lEJP+sWJ7I5Zu2YMbLqtCWtHAEYJwUEB5OACOEEv5AxRIShoWb8qEMjOUjBXbGzP0DAVpjwxus3BLf1YbKMRWi14+u4i0B6C01TyKTdsotpqHXyjmu19VdaRlDYm0ikRaRVpRkZY1tCVl7DxwEifOprHUpgBU6PXJ51uiAR6JtOrwfV5qRGZffvkq+z0/3JywSnFnUzNMOpwoG0pLgsBZ76HycAA8x/UJmk9JTJ4JITFCSLn5GcBXABwAUA/gzsxudwL4Tc+MkIGh9OAWzjPVNnie8ww9uoWaA1xnCFrVNU8VhOf35lfVMOkZbtnjppLF6nk1CAruoVGzSElXIep8526GNXVKXc/DS22j1MOQfqPYRUCKSXsAiq+2UUy1kGLTNhhtCUipGjRKcUZU8OTbR6BTICmrWL6t0UFlsFMvulsgxfQtdrqElxrRqrk1ePLtI1Zffvkq+z3/6RtNedU++oMvLBXaRhWA54jhtAQAv6aUvkQI+QOApwghdwH4BMBtPThGBoaSglc4r3pYGQhxpyXEQgKe3fOpoySySZGoQNAKJbZ0SNiwaBqiIcGxT+1v38dVowdb+7n1MWJQBH+/vdEK/bW0S4iFeEPJQtKgU+pZPMVRpMQlRK1pOkRF81T0cB4vIBLgHZQPUzUEAFMb6ALFLgJS7CImxW7fTXnGr+tTbNoGK5LiVNpY93oTvnPDeESDQg6VwUR3C6TY1TPsdAmT8mbe3+phMYPW9vIhvPDeSXx7VrVR8CnIIxbiPYulFIrse55WdYwYFMa3rh2DaLDTT5rtA7D674v+sSQmz5TSjwBMcdneCuCGiz8iBobShxnOe+ejVmubGYarGhBy/Vta1nDDZVVYumUP/vBxG64aXYHV82ogKxoSkrHqYm5fNbcGDz93APX7TmDG2ErcEr8EtV+73FLbqJ0zybP/+n0n0NIhYd2COCRVx73bG1E1IISVsyfi/h37HX0ARqgwp0iJpKEs3OniNE1Ha1LG8m2NqJtXk9PW6nk1+OxcqvP4TPnY8sxkuTwccFw/i/4C2KqLMZiwFwGxX+O0rPnCS7bTHkzMGFuJZIZn2tvbtyvPmNdn7fw4ZEUzqEUXgHSmsFG2fft17b18h/nM9HVomg5J1aFRirSiYdmsaqRlDSqlWDarGokMja2718f0LZqmQ5Q1y6/+7oHrIak6ls2qxi1XXoIHn+m8v2sXxK3FhBVfHm/4uq2d/njdgisRDfLdvj/mPR9aHsLKr0zEA0/vd7RdGQtaFEGT4rFs697cffrIBJpQnzKTSwXTp0+nu3fv7ulhMPRu9PjT7bed2ldcrYQ4QnIc3Op5NajbeQizJ1Vh2ucqHJPhtfPjiAZ5LN7U4HgpzBhbiZ8vmoa7bdvnTBmBFTdOwKjKKJrPpTEgEkAkkzDyy7eOYM2rhy3Os/0FYPY/dkgMd14zBuVhAUdbRax55QN8+/pq1NYfzOm7ds4k1NYftI5tbpewel4NKqJBhG2rHklZtcb4uweuxwNP789p68ffqMEDT+/3dPReSVI9mDzVa221I604bALotBU/Jp+ipEJUVCTSGi6tiOJYm4iyMI9oQPBngpiRKsyegFZEg76035FW8Mu3jmD25OHW6uHOAyfxrWvHXPD1Kfa17+bkqEdt1U+f2pFWQCkQ5Al0Cqg6BaUUAZ6DolNsfPuI6+R2SCx0Xn7BvI9Dy0P49vXVuHRwBClFg8BzuGez+/0VZQ2xoIDFm3bn/H3DndO7PXk273lSUvHQs+/hnY9aMWfKCDx400QMjgahUyPikZYNOks0KKDpVMKa0F9o/xcRBd2gXn8WDAwMFwb7iqt9IlwZCzrCg8fPpEAA/OS2OE6cTSEa5C16RkJS8fbhFnxl0nBPOoe53WtS/MhzxsR21dwaNLUkczKzzf7r5k1Ba1LGPZsbHCvMIwe7q3CMryrDj79RY43dDK//5LY4JjzyovVir4h1qoCMyKPoseHO6a6TX68JQ0U0gDZR6dOrLN1BsdUqQgEOZ0SKh559z7rudfOmYHDUn1SeYtM2okE+Z4K1am6NL9SHYl/7/l4kJRYSoGsUCVlFeVhACEAirSIc5BGisIqY2G3nfP2BrlOLXrbiRsOfbvnbq/Hwc+85ikSZMO+vpGrQdB1VA0I5f78Q2zLveWVZ0KKN/ONfXAbCwfqRmS86+MJ7J/sUrackEgYZGBi6j+ySqXYtUDM8KMoaHnh6P65Z9QbGPfwCRFnD4k0NiH//FRxuTmDJpgYs/dVedKQ71TJMmNnd5navREAzGc9MbgE6M7MTadXq/8OWJO51Kenq1Xd7SnGM3VQtaDqVcCYz2bLOvcT7zbCq20suX5JUf0+eckPR1TZkDSt37HNc95U79vmmeFJMNQzAGL9bGXo/xl/saw/07yIpSUlFStVwVlSQlDR0pFWcERUcbRUtFYr6fScs26mtP4iUcn7ZmqKi4WiriHu/PMGyk460guZ2yaFaZOKq0RU42ioikTaSCu/98oScv1+obXEcsfzot6+vRlLWkEhrVgLj0pnVnsmMfU2NiK08MzD0cXglxzm0QAM8nlg4FWdEBZdWRB0Jg9XDyqzjy8MC1i+cirOZ/Y61iSgPC4gGeKyaW4MHn9nfZdlv87PAESucuedoG35y2xTc99Q+z+PLQgJWz6vJWdV4fu9xq2/79rqXDzmOj4UErF0Qx/KtjVZhFXtbaxfEEQlwSKRVcJxR4ty+ouaVJJW9ymcm8kSDvJEw049W5OyIBPgcWxkUDSDiUxZ+0XWkgzzq5k3Byh37HCvbfq2eFXP8kQCPtfPjOdEmv649UBo6z8VCROBBOCBaEUFGyADl4QC2/M/H+KsrL8GvFl+No60iHn/1AzS3G7kb56s+EQ3yePzVDxyrzGUhAavm1qAsJGDdgjiWbXXmmKx5xYi4AQAhBlXDwXn24f6b7wqe44wEREmzVrmzfbfpC8dXleFnd0xDROg767Vs8szA0MdRaPKQrOlWCPx3D1xvJbyYpbrNsNwDN33eESpfuyCOc2kZdS8fwmO3XoFUnkRE83NHWsGhf7kZx9pEBHkO144bioSs5j0+regI8Bx+dsc0lGW40Gaxlj1Hz+KxW6/AqMqoxavO1qJu6ZDAc8Bjt16BSyuiOJ2QrLYSaRVPvn0E615vcnCvjRefQcEQFfdxmat8Jgcwm7LSXykcqqY7bMq0FVXTIfAX/hK1X3cT5v3wg9crKTpCAWLZy7E2EaEAgaToiIZ69/jTqo6GT9ocqjjvfHgaX5owDGU+XPv+kBDmBV2nSMrGCr6k6SgLClB1ipRiJFMvsdHN1i2IIxYUEO7GDwtR1tDcLqGlXbLs5MOWJHYeOIlFXxwNnXb6sqZTRuGqlg4Jx9pEAMCQsuLRamRNx7KspHGddkb0+oMv7Ds/AxgYGFyheZQxtpeLNagHnVQJ3abnbC+XvXRmNe57yhkqX761EQLHo6VDgsAT6FTP0a/N1mn+p98cxLiHX8DMul1YumUPUqqGpVv2YGbdLjz83HuuOs+EAFf/6DUs2dyAlGxIILV0SBA4gpYOCdEgD12j4DmCW6ddknN8LMjju79uxMy6XRj38AtWW0lJxZLNDVjz6mFPzWdR0Qoqee5GWemvFA5Fp1i+tTHHVhSfCmkUW4dZp9RhLzPrduG7v270rfx3MccfDfCYProSS7fswYRHXsTSLXswfXSlb9q7/ZmqZGotnxEVLN/aCI0aE2e3stzLthr20p3JoulXQGDZyfpdTbh12iXY9N8fgwMQFDgs/MW7+It1v0NLh5EoXRbmMTgaQDQoFIVWk/2uMP3lihsnWBG9/uAL2cozA0MfhxetIBYSLIpCNMjjpslV1kqVKGnY/Umr9d2kbYyvKnPVVy6PCHhi4VSQDA9S4J0lsTlCLJ3mR59/z7EqnE19yE4kPNzsTNT6w8dtiAQFBAhx9BEReAgCB44S1O3sTPT67FwqkwnuXcq2K5pJNMiDI4WVPO/v+rcmCqELXQiKntAXEhzPhKlX7lf573CQR9PHHY7ox56jbbhuwrALbrvYCX3RoIeOdD+wc1NrGQCqBoQQy+jBEwKHLf70jSYjSa5Ae3GjwVTGgqCgOHE2jV8tvhqipEFSVfzV1EtQURZEStYsPX1R0sARAAQI8dx5U2oKoeHoOvX0caMqo1hzexxp25h62hcWk1rEJs8MDH0cXdEKVs+rwYCwgJsnD7f0m5fNqsb8L4zC0i17XDWRs/WVE5IKSdUdHMvV82rwj88fsKTjCIwXQXO75BhfNvXBbLelQ0LtnEmY/fibmDG2EolMstNVoytwJilB0+GqIJJSdCvRy+18s8fuFT53aEbbEgndtJ3N7QmPtvqL/q0dxdYavhg6zPZnwk8dZrP9y4cPdIT5/Wy/mDrkZvnvnHuraIj6MPbeDFFSkVI0izaRljXImg5Z1VFbf9DhZ6qHxgp69vMp+bSKskNT2cjz+BRz4iMxs26X1YYpBRcV+POm1BRCw7FL1bn5uKOtIr685v9Z9CyA9KgvLDa1iNE2GBj6OKKZ5KF8JbEB4lDkmD15uPXdTttwKwe7el4NBEJyFD2yy2VrlHqWJA5yJG9J7rXz46A6tcrPChyfR0EEeUOH9rFn0y7c+j6fRBtWtrsThdCFLgTFpm0oOnW1Mb9oJ8Vuv5godvnv3gyOEESDxmqzqlOkVR1nRSXnXj74zH5885oxBT37+Wgw2dQns93B0YBnCe/zpdQUcoy5z5pXPnD11Wte+cBBz+I49KgvLDa1qG//RGRgYADPc6iMBV1LYpsUjuxy1/asaS9NZJPCYYbKu6I+mPSKtKK6hqoHRgT8bNE0lGX24zmD6mEv771+4VQ8v/c4Fn1xtCcVRZQ0NJ3qsMLtXmO36zm7lcNdc3vcKihT6EpFf9e/teNi0DZea2h2LRXvB4qt5lHs61NMREMe9CSfyn/3ZoSzaAe6TjEo6u5nysICQLsuU51NhbD7s3ztuvmZQqhj2XSGSIDr8phIgHNQ4X78jRqMGBRBSnan4oUDPEI856DWXcyiUsWm0LGVZwaGfgCe51AeNrjMpj6oSWmorT+ICY+8iNr6g1j5lYmYM2WEQwfZSxP5cHPCoX3rto+d+nC4OYFfvnUE4YCAJZsbMOGRF7FkcwOqh5VDVjR0SCqWbDK2372pAYm0ik3//THi338FLx1oxuHmBJZu2YNZn69Ch01XOvs8Fm/ajcuHD8Sm//4Yh5vdx56UVEcSjRXipkBK0XHXxt3WONpEBfp5rAb2Z/1bO0zaRm39QUx8NGNfsyci7ZPWq71UvJkUd8NlVb61X2yt5GJfn2LCrpluoq/p+HpBVjSoimYsBMga2pIyjraKnrbSmpSxOONPFm/cjdaknONP7NfT7s+8/Jcoa55+pqt7Y9IZsse0bFZ1l8eYtrpyx35QCvz09cOeVLy0rKFNNCok2n2pWbSrq2tyoSi2jbLJMwNDP0KhlIadB05a9Ap7BrUXpSLoQsew77Nqbg1++kaTgw5iD/cqem6If/m2Rtxy5UjH8eYY7fQPt/NYvq0RsycPx0/faHINMXqF9vuzioDf0D1oG36pVZQ6LaTY16eY6M/0JEWnkHQKjhBo1KDeuFEZ1i6II8CRgvyJl2KPm//q6jp3dW/cfNzyrY345jVj8h7jRh+585oxCHDuz4lGaY8WlSq2jRJaAg+qn/Czvj1Dn0WPLxUWywXHvAEAACAASURBVE51SvHmB6cwdVQFysICJjzyIlTbL36BI/jghzfjcHMC//PRacydeikiQR7tKQUCT6zwG08IwpkiIFSnKI8EHO3atx9uTlh0kA9/9FXc91Qjls6sdoSq19wex+Z3PsbX4yNzQvDnUgoEjmQoGQalwuw7yBEEA7zneVAKS21j5OAIDjd39se5TIJ0Sj3byt6/lxSJ6LW2qlOKFdvd77XbtT9fnM+96m77xR5/MdsvNjRNh6hojpA8n19DukdPyg+fquvUOgtKKQgh1j0cNzSGRCZZNZWhQhCOOGzUXjQk22foOoWsalAyihaibFzb1oQEQggqYsFORQ0gr3Z0Pt+U77kR5dxjzHP2Oo+0rEGj1KLMARTP7PkUd8wY7dlPMZ/bQq9DHhQ0iB4jVxFCopRSsaf6Z2Doj7Bn+NfOmeSaDW3SMWaMrcSfjx2Cn77RZClWVA0IuWbZq7qO6mHlDuWA1fNqEOA51NYftPpoS0qux3spGyiKBkXV8XdZKh51zxkFTNbOjyOg6F1mf6+eV4OTZ1PWeXllfJuhvq4yxPtzkYhCcTHUNopZJKXYah7Fvj7FhK5TtIlKv7J/85mPhXiDxyyrCPGc6z2siAbB85xDfaeroiGUUrRLKra9exS3XHmJtd+yWdWYf/Uo/PWGdx19lIcElIcDrtc7n9JKIT7O/N9NYcN+Hl7vg7+oGZ73+bxYKhzFVJy56LQNQsgXCSHvA/hT5vsUQsj/udjjYGDoj7Bn+HtRGux0jJ0HTjrCiEtnVruGmgUut0CAGYK20zmCgvt+XsoDsst2u4rH8m2NEHj3sKE9+9sYC7oM3RUa6mP0jq5RbFqFl3JLwKfJW7FpG8W+PsVEf7R/85w1nULNFADiOJL3Hp5PASWTGjF78nDHfrMnD8+hTNy/Yz/OiEq3rvf50BnsCht186bknIfX+yCR1vI+P32B8tMTP2//DcBsAPUAQCndRwi5rgfGwcDQ75CvGIkoGTJvZjGTZ/Ycw+zJwzG+qsxRLMItg7k84iGIHxKgaBT/ced0K0vdS8HgfLZnq3gEOGfBlGf3fJqT/T1ycAT/8c3phpwWgVUgJhzwLnhSaHa8db79oEhEoSi2WkUwwIOkFcd9T8sqgj69hEtdzaOY6I/2b56zeX+68ltArvpOvmtmtmVXOgKAcUNjrsVXLq2Ioju/48wxmb4wGuIzdAv3c64aEMLSmdWoGhDCEwunOXx99ljNczLH9lpDs2sRo3CAL3lFoh5JGKSUHsva1Hd/rjIw9CJkKwjU7zuB2vqDhvpEWEA0KFi8s5cONGP242/iTFKyKBVe2d/tKcVTkePvfrUHbaKMFdsbPffzUjZIpLtW8UhKKk4nZUdW9w2XVWHOlBGOY0RJQ1LSsHjTbkuVoy1pjMue8V2IWkZ/VhsoFMVWq1AVDRTEcd8pCFSfVj9LXc2jmOiP9i9m7peqaJZf8vJP9nto+pOurplpD3Z1ozlTRjhULkxFpGWzqnGsTfSc9BaCbF/opnhhFsOprT+Iz//jS7hnS4ND6chLielYm4ijrSJuuKwKP32jCeMefsFSZsqnFFJKuOgJg4SQpwGsAfC/AVwNYDmA6ZTS+Rejf5YwyFAAevxJLpadmjJB2ZX5KmJBpBTNSvoRZRWirCKR1lBZFsTdmxo8eXur5tbg9T81Y9bnq3K21718CACw4sYJGFUZRUu7hFiIx+mEjEsrojjWJmJQNICyoIC2lIzlWxstnt83rxljaUE/+fYRrHu9qZPzvPOQVbmwIhrEL373EWZPHm6tcOw8cBJz4iMtzvO6BVciFuJx15O7HVy7GWMrHVUMN9w5vSBuXC/iPPdaW03LKtrTao6tDQgLvlTQ60grll2amDG2Ej9fNM0XTnJHWsEv3zqSY1ffunaML+1LsopUpsCG/VmICBxCvbxKn2H/EpZtbbTZfxyVsVA++y/phEFRUqGDglKAI4CmGxSIhGxUV40FBURDPBJpI3lSEJxrk5qmo1Xs9HHZPsP8u53zXDtnkiNnBDBs/Ik7pkHXKUIBrlsVHROSisUbc31htv9LpFUs3tS535wpI/DQzZ9H1cAwjraK+H8fnMINl1XlcJ5DPIcf/Ncf0dIh4bFbr3D44RLgxffahMF7AKwFMBLAcQAvA/h2D4yDgaHfIbtgSlJS8dbhFnx3a6OjxHVI4HAmSfHQs+/hV4uv9qR6HG5OoO7lQ6jfdwJ7jp7N2Q4gZ7K9dn4c9Y3Hrcnw2gVxHGpux8jBUTx26xW4ZHAEbUk5p2zx311fjZYOCeXhAH5yW9wKA/7ktimOBBtz4j5ycLgzgzzAA8SdMmKngBQadmbFULpGMMDjxd3HSpb2EA3yrnblFzWB5znIkoqHnn2v084XxEumjHuQ5/DYrVdYE/9gfqWNkoam6QjyHNpSMioiQbSJMrb9/igWfGEUBIGDoulYvGm35w8JM8Fy27tHLRpDUlIRC3b6DJ7nUBkN4lvXjkE0yLsWtQIyNLmwgBXbG7Hm9ni3zqdQ2o29GI65cLLiqX2O8ywLCdiwaBqiGbWNcykZP/ivP6J+3wkIHMGoyqjDD/cVH3nRrZ1SeppS+teU0ipK6TBK6UJKaWvXRzIwMPgBs2BKUlJx96YGLP3V3pwS16KsYeWOfXjno9YcqoWd6lFbf9CaULttz6fBbNcYHVUZw9ItezCzbhc+bEm6Jg9+2JLEjH99HYs37UbTqYQjDOimVy3KmiMsWEghl/MJO/eF0GMxkZRUvHSgGfHvv4KxD71gFbvxi5ZQbNpDPrvyAykX7dzlWxuRKoGkO1HRcE/meR338AuYWbcL92zZ02cTBkVFQ0o17ldK1SwflpQ1nBOVnKS5ZVsb3Utbv3oYsx9/E+MefgFLNjcgpTrrmfM8B0IIjrWlcPemhrw0OdP3det8CqTd2PdzT3hsNAqkEAJRNmgg16x6w3onWAVd+qCP7Am1jXUu/35ACPl6AcfyhJC9hJD/m/k+hhDyLiGkiRCynRASLP4ZMDCUHnSdIiGp0Gnmf53mrGrUfu1yrF841Vq5W/K/xmDnvddhQDiAn90xDSu+PN5RACAi8K5qBxGBx7r5cexaORPjq9wTSsZXleHDH30VO++9DlUDQo6xeCWhVA8rw5wpI6zV7V0rZ1rjLWQFMhrkcwsZzI9j3NAYdq2ciScWTi25jO/ejHz24Uv7AY/2fbqHF7M8d/az4Ac0TUdHWoFOKTrSRmU3v9DfEgZjIcGyB/O+VQ+L4ZLBEYyqjHZ5LdyuV9WAEEDReX90HQlJRUTgMKQsiCfumIZxQ2N4PMvG1y2IQ9dpl/7Kzedb4ylQccO+X77kwGiQ73eFc3oiPhQG8HkAOzLf5wI4AmAKIeR6Sum9eY5dDuCPAAZkvq8C8G+U0m2EkCcA3AVgfXGGzcBQmvDi54YDnKW3Wfu1y/HVKzp1lpfNqsb8L4zK4av+3fXV+PRMCjwh+NXvP8G86Zc6KCA8R6DoOhTdoHz8+Bs1rpqezefS+NKP33Bo25r7nTibcj3mdIeUQwH5t9vjCPDuuqXZerwpRcfzez81Jt/DypCQnFzqtQviiGUSBhkuHKquoywk4Gd3TLO46wJHoOo6BB/WbdKKhoZP2hy0kHc+PI0vjR+KMh8oBMXWkS6mzrNXbkNlLNhVIZOCUKgeel+BWQjkrQdnIiVrePQvL0NKNiJ0hVyL7H3mTBmBlbMnOqgeq+bW4Pm9n+LOL46GrOkWn3zZrGrrGTraKuKH//VHNLdLWLfAm7LRVU5GobQza79F05HyOM+EpCLAE0SDQr+isvUESakGwPWU0n+nlP47gC/DmEz/FYCveB1ECLkEwF8A+EXmOwEwC8DTmV02AriliONmYChJeGmy2nVyb7lypIMq4VZG26ROzKzbhe/8ei++Hh+Ju57cjStqX8bYh17AFbUv464nd0PVKe57yqB8cASuWp86pTm6qOZYvI6JhficsOHfbzfC3G4rkG6rKAuu/hxq6w+iPa1gyeYGrHn1sDNkrvbNsHNPQNEp7tq4GzXfM+yj5nsv466Nu6Ho/iSpc4TgiksGOdQwrrhkkG9VykpZ51lUNNfn1y9aRX9bZdQoRdOpDsRCxo+0RFoztJ49SnOvW+D0P9nXa8WNE3Lu/YPP7MfsycNxRlSwzEbnWfPqYSzZ3ICjrSJm1u3C840nXKkhdhSiw10o7YzjCECA/3zroxw/u2puDTa+fcSQ/zyPNvsCeuIn4mAAZQDOZb7HAFRQSjVCiJTnuMcBPACgPPO9EsBZSqlJcPsURhJiDgghdwO4GwBGjRp1YaNnYCgS/LZTe2nS2jmTrBLZgBFuCwZ4VHCctXJshpCrh5WBEDi+20tcN/7TjfhN43EMiAQc+5jlhe3h7j8bGMF9TzXmaH3+5LbOVRMzFNrwSZu1wrJie+cxZt/RkID1C6fi+b3HUfvb961jK2JBnElKlgapV6ngQjRXYyGjtLjXikkvKcnd4yjEVrNtym4ffiAc5FH33CFXHVm/2m/6uMOxcr7naBuumzDMl/aLSQspNuWE4wgGRwKOqFNE6H3Pgl8+NRYSMO+J/8EHP7zZpm5BUTtnEsYNiUHSdGxYNB3REG/5H/u1yPY9gHfyMqU0R9eZI8CQshA+euyrEDOc/khQQErWLHlNO/ym1USDPNa93oS/u77a+by9fAgvvHcS37lhfLfaLWX0xOT5xwAaCSG7YEiCXAfgR4SQGIBX3Q4ghPwlgFOU0gZCyMzz7ZBS+nMAPwcMuZpujpuBoajw007dwnar5tYAMBL7rhpdgbRi6B4v27oXGxZNc4SQf//wDdZ3swTrA087FTNkxT3sbA93nzibci1xfOJsyvp+1egKdKRVq7x37ZxJ1jFu0nhr5xuTo9rfvo+rRlfg+JkUvvTjNyyppXwhdXNlpCOtuIYg21MKlm7Z4yqp1Ivk6XochdjqxSjPXczy2fZS9tl274fUXjFpIcWmnKiqjjbRRfIyGsyRaOtJ+OVTk5KKHff8OZKSikRaRUjgoFKKj1o6UDUghISkOuzcTbbPXio64XF/PjuXQoDnUFt/0Gqrbt4UhALEQfFYPa8Gjz5/IEPfyPVBftNqzPZOnku7SueJkoaycN+j6+RDT6ht/AeAa2CU534WwKMAPqCUJiml93scdg2AOYSQjwFsg0HXWAtgECHEvGOXwJC+Y2Do93AL2z34zH58+/pqK8Sq67D2SUqaI4zI85z13a0E6/Jtjf+fvfePr6K68/9fZ+b+vgk/EiHLD1nFAFUhBEjt8rG1iLWA7qIfLRoeRbHbgrJ20VLUtrLbbNfWKpQK++gDf2y3gOyioi1mvxUpVmm3lo9tAuGXXSEIooABEgK5v+bn+f4xdyYz987c3CQzSe7NeT4eeRBu7pw5M3Pm3Lnn/Xq/3pBU+7CzOdztJMEI+DhL6E+UO/dvLhvu5NZx+7QxRlsc6brsdiZOpZ237zvlWGp4MJYk7g1el5/2WlbhVDLeLdlJwGEMBlz4Iub1udEdJzLPTbHKnnhCUDmyFDwhKA374fdxeGhrE2ZedRna83DbyMRO9vLUnVXgCMk6ryu37UcspWTdR8tmVTrOQW7LavT2Aj7OdlxxA+f7Up/R518VCCHfgJb4NxZAE4C/AbAH2gOxLZTS7wL4bnr7WQBWUkq/SgjZBuAr0B6oFwN43dPOMxgDEDspgVPYbkJFCZ6/d4YWYuWJEVYfMSRokXaUhrp2v8gMDc+fOhoP3liJUIBHGTq9pM0SDHNo/cgP5+FSUsL2fZr3r5OXtN2+h4T9qJt/rdHWzxfXaA9lRCtuEfbxSClqlrxCUVQkJAXRoA8lFHj2nhkoDfmMfpjlIFmep4PMYaC39IVsw2tZhZf99zuUF/e7oBv2WtJSyKXFe0IowEMvKCdIKkLp4x8S9qM05O/2vMBxBGURq+wlEuBBCHF0tMh8LZc/vds+9Hp7ILCV1IX8fE65WzHSHyP9IQCfBfD/KKU3EkI+A+BHPWzrMQAvEUKeALAPwM9d6iODURA4SQnCft42bHe0JYa6+sNYV1uNoSFfVlhdl3bo3s57Pmw1SrDahYD1183yCl3m8ci2AxYJhs7M8eU42Zowqk49dWcVPr1oddio338a5zoEPH/vDMd961UBE4KMhKgYIWQ7p5D1C6dheNhvG2qWFQXf/K+mLkOcg81hoLd4LdvwWlbhdf8lU3lxc/8lSel1hcGEqNjed26NVa9lIQMNSVKQSnsyx0UFYodgyLzaE/YSsFznWi+aku+8/XFbwrK9nT995r7MMhE3rjnHEcRMUik7Sd1gkrH1x2J7ilKaAgBCSJBS+r8AJuW7MaV0N6X0b9O/f0gpvY5SWkkpXUApzZVwyGAUHU5SAo6DbVjwZ+80GyFW0UZ2oUs79hw7b4SUN+xuzgrV6X69+nvM8gqzzMMswTCH+dbuOmLZp0qz5R3raqsd5RW8KRSZGeq0cwpZvnWfY6jZx/FZ++7K83QwOAz0Fq9lG17LKrzuv+jQf9GF/ns9Vr328B5oiCrFhYSECwkJ335lv+GwsefYeQyL+G3mj2y3HzPdmbfX1VajJMRnzaEbdjf3+RxkHlf2RVMGj4ytP5ZLPiGEDAOwHcAuQsgFAB/1Qz8YjIInU0pgSCfSk6meAW4uow3Yyy701ydUlGD0sBDCvs4SsSlRsYQYgxwBxxMMCfmy3DrMUotMCUZCUPDa3o/x4I2V+Ond1UYofMzwMM60J/H0V6owZni4M3ufJ3j/eKttaP6Fe2vAcVrI0Hwc+cpM9NdLwz74fcQ4V116nqZDoSlJ0SyaCBBLyUZfBrMLhxmvZQ99UcSkUNu3lQW4OCZ9Pg5lkUCW28ZAShZ0C72glO6y8ecTbZDTX3AevLESJQEfAjzXOX8IMiKB3DZtThKwkJ9HkOes59XPQ5RVS/scIVh7d7Wnc02mHDCcLkMeDfBGX+xcnMwSkmJ2J+qPhMH/Syltp5TWAfgnaFIL5s/MYPQAc/lUPYxWV38YEx/fga9vbEBSUrLKaANW2YUZXdqxdHMj2hIifvGH41jxchPaEiKWbm7ExMd3YOnmRpyNi1jxchO+trEBF5MSkukQd1394aySsnrZ7lMXkhBlBTddXYG6+sOYtGoH6uoPY+WcSWiNCbj+qXfw6Kta+ePSkB8+H4eUqBguHBMf34H7X2xE5chSpEQFSUnB1zc24NSFpGV/uswk87hylXOOBHwoCeXneVoS9AEUiAtaOdqJj+/Aks0NaEufkyWbGtAaFy0VvQYjKdOYMF/rlEvlrb0uz13I7euyAPM925aQXB2TPh+H0pAfHCHG/VpsqKpW/S8uyGiLC2iLC8Y1q99/GnOe+T3u+Y8/4WyHgI6UpMknQv4uHxAdy2MLCmKCDEFWcLpdK9H9mX96E1/f1ICEJIOqFCUhPyIeeynrcsAlm7T57T/+50Mk09KVtoRozHt19Yex8suTMH/q6M5jSN/fmW0U27zYr6OdUvo7Smk9pVTsz34wGIVKPmE0nthLH8I++4xvs7RjzuRRtm4b5mzvR7YdgGKSgDhJNTgCi4uHua2Aj7cNQeYKnethz0xHj52HzmQd7+oFVY7uBj0JedqFXbvKgB9seC178NKtAnB2ZPG71L6X/WfOMO6QkBRcSEg415FCNOBDNOCznVtKQjyGhP15zyVOshqOAy4ktCIsWQ5HXTh4uEnm+JkzeRRkldo6i2S6OOnnoNjHIMtyYTAKmHwKf4QCPAKZocB0iNW87akLSXAE+Ond1Xjwxkps2N1syejObHdCRQl2PnwDNuxuRknIGqKPpSQ8d+8MlAQ1I/+kpKAsGkBCUFAxJJjVVmla/mHniuEU2tZDhnaFWHYcOoMX7q1BOMBbnAbKTechJSpQKQVJJ8J0J6TodK5zZcAPNqJBH+7/4pVZkptCcKsAgICfx46Gjy3lv19v0pxh3MDv5xGUrXIoVVVd6T9zhnGHSIDH2OFhXEiICPo5EEIQ4Dn8fHFNunCTJqNo+EiTkuVb3dLJDYOC4rKSoKMkoq/cTPTxo8sAK0dGQdIRBqfPghcW1yDs4wyZBihs5/piGYPs4ZnBKHB0KYGT8X5C0B5enYp7lAR9SAgyCAFWZjgLfHoxiZhg7zKhO3esXlBlyDYe2XYAcydXYF46ac/svGFuV6WdeujPXlGGjqSMB7Y0ZrliPLvI3m0jlpaiPHVnlWMhlr8Zf5nxmtlpoJTnoKoUcdH5nHSFk/NGVxnwgwnJwQ3DDTcJvX2v3CoATVbx5qEWfL/+feO1mePLccf0se4UGpEUCDLFQy9Z+x+WFAR667bhcM8OxmIWvUFMSxWGBn1ojYsYEvQhJatZRVHWLey+y0umG4Yuc3hoa6cbUGZhq1hK7pOy1wlRwfLZlbh92lgcPt2O4VE/EoK2YuzkshIN+LKcn+zm+mKZFwl1KYRWKNTU1NCGhob+7gZjYNPvGQ09Gafa5Ctg+VazRVs1okEfvr6xIasq1AuLa4xJrCOl6SMz37P2rql46s3/xaq/vRqxlILLyyL4uC2BaIDHv/76L6jffxozx5fj+Xtn4Bd/OI45k0dhzLAwlmzW9rfz4RtsK1I9eccUw6puXW01yqIBHDsXx85DZ/C1z19p9KVx1U1QKCwfKOsWVmNI0AdBoVAUFUMjfrTGrBZ0GxZNT6+UaF8MKLSVUH2FJyEpWLLJ/pzof8+V5GJnEbh6QRXW7PzAseqXRwzYseo0pp6/d4YrD58dKckYc3rEQR8/brSfEGS0JcSsL35lkYArVnVenp+EKKMtbtP3aMBUXrrP6dex2pM5tSMloTUmorwkgKWbG/H8vTPQGhPx3V8edP26xQQZSzY1YERpEI/NnYSh4YBR7jvs5xEXFPzx2Dl8YeJIY972KiFPVSligoz7X2zEhkXTsWzLXowoDeKfbr0akkrx7Vf2W+bj8kgASVm1nVPNc32BWNnl1bnCf/xnMBgGAZ7Dk3dMMR5yAzyHoI/rMoTrJI+oGBrCmgVT0RbXPjDMJWMz27p92lg89toBbPnG57ossDKuPIIjP5yHmCDj3aPn8I9bm4yVFnNfhoYCiIly1jH5OA5f2/gnrF5QhR+88j7GXxY15AEpUUFMlPHQVvuV7/ULp6Es6lzYoDXWdQnurLCroIDj4HkGfCHhtVuFecyZV+rcCgsXcqGRkJ/Hmp3e9X2wEA36DNefuZMrDNcNL65bJMCjYkgQj99yNQRFtZTjXrNgKl5r/Bi3TxuLsF9LVXPy+Hfj4ZTjCEpCnYVgdIeR6eOG4bZpYyzzcZDX5CxOUiF9ri+2ebH40mMZjEFKQlLwwJa9mLVmN6763huYtWY3Htiy1zmz2+R6kMt549i5uG3J2AdvrLS0pScrmt0unJwvjrbEcLQlhvs3N2LZf+6zJJ+Y+5KUFSzLOKZlW/YiKSuWJL21bx3F/S82IiEqUCjFQ1ubHEuLL9+6z/GcxAU57yQXPezKEe2DJhLwNgO+0PDarcI85szjJ+Gim4cuB7rqe29gzjO/R8sloSDcNrzu+2AhLshIygouJSXcVj0GcUHGx20JT65bQlTw8JcmIi5mJwuu3LYfcyaPsoxvrxPy9DlSL5gFADOvugz/YPcZIyk5P2eKcV5kD88MRpHg9M0/GvTh2UXTsXvlLBz70S3YvXIWnl00HRE/b4Tnwn4e6xZas8h15w2n1eMJFSXY853Z+PfFNZZVNLPbhl2BlTULpuZsNxLo7EtXq3N6kt78qaNRN/9arcQttFWiTM/pzO2zihEsrEYkoCXq6NZL5j4xukfY71BIw6WEPrOP9LEf3YKdD9+AiiFBV1e2M11j3FzZjgR4rFkwNevecKN9r/s+WAj7eESDPpQEfRgS9iPs4zE0z6Io+tyq0vS/KrV9TSfi5zGuPILLyyKOycjmuS9XUqjTPrrC3D+OAM8umg5VpVifno9zzdmag0h1l+elWGCyDQajSHBKYktJCkRFtcgu1i+sBqWdJWIrhgTxT397jRGO60hJ2PzHE6jffxoP3ljZZcKgovqN9+jJIU/eMQXjyiNIigrWL6xGWTSohfn82uqDU9nvCwnJkJ84lQGOpWTj908vJi1lYs3luevmX+tYOtcsu4ilZGx89zjWv91sm6hTLEkufUlKUtD4UZvFrWLPsfP4woQRKOF7v27jdfnshKhg+75PLNKH7fs+SWuqe99/QVIR9BNrCNxPIEgqIsHetZ+UVNu+//0XxqOkl20PFlSVQlZVqIpWzdLPa648L713EnfOGGsUCmmNCYgGfOBNY9peUlGNAM/hgS17bWUWHEcQS0k4HxMdk5HNc5HTfB9LyZYk3XylHJl9Xj67ErWfG2fI3568YwqSDvvUJRl2ssFihSUMMhjZ9HtsqecJg9kauLCfNxL4dPQEFz1hKTOxb/7U0Xh0rvZgYqcbfurOKqNioZ5olxBkS9Le6gVVINAcPOySSJ5564jtw8/wSADfSCeebLyvBteMHmppd11tNd4/cxHP/e44Vi+oAqXAo6927sN8LHrhGLMuNvPDxClxq27+tairPzzQk1z6vVNOY7WQE+4AICXKuJSSs8bekJCvW64KTnjZfy/1sL2goBIGY4IM/fnoF384bklk1pk5vhzP3TMDPo5YxrSe/Gc3781as9vymjlxOyHKSIgyUpJqdfOorcZLfzqJ2s+Nw2XRIDiO2F7jdQur8dJ7J7H2raOO+8h1vOY+2yV7r/jSBGNhwvyloDwazJmEXWALDyxhsKdc8Z1fd+v9J358q0c9YTDyxymJLbN8NZBdrjozHFe//zQ4AsMrOSHKhh/tpaSE7ftOZZVkbTjRWUY7LsiQVYqhYb9tieZx5RH85K5qfHqxsyT3mfYkVAqEAzzWpC2ORg/TPFb/fbHWj7ggI8AR3DBxJK67ohwKpRbP5/r9p1E5ssSyT/M+7MoUR4M+zJ1cFIs1aAAAIABJREFUkeXnq3uXFlOSS18SCvBoPtFhW1rdDbwu/x3w8zh3LmbxYT7ZGsdlpUNdad/L/ntdnhuAxYtdb58vopVGs8Rl/dvN+OZNEzB3cgV+vrjGmHc6UjIigezz6iSpuLwsYnmtYkgQoIBKKRKCgkiQx/d+eRCPzJlkrGyfupBEeUkAcyaPQnk0oLlrpK9lpld02M9h/dvNWfvNR66T2Wc7icb6t5vx4OxKU6lwxTh+r7zFB2qJb/bwzGAUEXoSm6pSw9v56a9UOXpz6q+f7xCy3qMnGL3a+DFumTLKstrw1J1V2Huy3ZA1dKRko4y2eZXRz3O2q8tn2pO4/ql3ACCt9ayCogKPvda50v3oq9ZteBJAUlSw1ME/WpdafHox6bjPldsOZK3AiZKCeZNHYZkpnLquVvNtLbAVkwGF6ODz3F0/XCe8lm2IkoIRpaEsH+lC6L9enturlWdFUTVP4oxV+fJooGgeoFPp5GMA+Le0j/Od08ciJmRHI4aFfIY3t64btptzP25LGP+fP3U0Vs6ZZHHVePaeGWi5JBhzI6DNj09/pQp19Ydto2Fmr2hHr/88ZGdmGcj8qaMRS9m3FRcUS6K03fbd3bcTAzSCAoAlDDIYRYk5EzuzfLVeUpYnxEiaiwZ52/dEgzxunzYmy23DXJJ19YIqiHJ2hvgj2w5AVe1LNHOEWPajUhjOCU7lwEWVGv2we4/eJ44Q+75Q2GakS6Z2jVK4LzVB6kaiDSMbr8+r6lD+W3VJiuh1/70sX+65E4Ok2J6bYim9DGjXR5JV8ITg+gkjICoUssOYEExjIiEp2Pju8ayEzXW11SgJ8cZrK26emHX9N7173Lb8d8DHGQncua6lU9nvfJL2zNs+eGMlNv3xOJ6pzU4i3/jucdf37cRALvHNllUYjCLCHOLKVb7a8HxNSzMiQR6rth9y9IV1ctt47p4Z4AhBJGgN2ellXXWv0MxtK4aGcOSH8xAXZPg5goBJWuKU0V2SQ2Zi7pNTf0cPCxu/RwK8ca5yOXrkChkO1HDiQMFzn2eH9t1YdQa877+X7XtdntvrczMQiAZ9UH0UhANCprLbXR13JMBj/dvNaD4Xt8ynZdEAVm7bb8y3dm2tf7sZ/3BjpSEzSwgKBFlG0MfjspKgYQ/6xsEzttfSqey33bxkN3+Zt711vdYXy2fCbz7AGwfP4Js3TejVvvNlIJeZZyvPDEaRoIe4lmxqwMTHd6Cu/jBWfnkSPr2YtPV8PdoSw9c3NiApKY6+sCdbEzjaYu/VHE9XoJpctxMdqU7PWj1Jr67+sOO2J1sTmPj4Dizd3IhLKRmtMcF43+n2pOP+8vGPPtlq78NqKZ0tKMa5iqWc/XbN53PJpga0xkXDcsrpbwwNz32eHdpPFIAPs9ft6+W5M9vWSyz3Fq/PzUBATLsUdaRkJEUFMUG2eB7rZB63Ll+o33/amE/r6g/j2Lk4Wi4JAAE4Qhx9kc91CKAU+OoL72HV9oNISiqWbG7EpFWdc/ry2ZWOfuYW/3kHb2Wn+QuA4eSxfHYl4oKCuvrDxmeC2X2op/vuDvnUKOgv2MMzg1Ek2IW4HntNkytkSjIyQ4B+jtiGC9fuOmLxbTaHIANcp+xDlBVjHw/eWGlIMOy21ds1hz0Dvk5f2lwyE/11O/9o/ZjW7jpiu/2G3c1GKJHjYJyrvR+12foRBzjiGDIcyOHEgYLdmFpXWw2/S6vznGk8mK8zR9xp3+v+e9k+x9nfQ5xLn/gRBw/vYvL0lVRNptGekJAQtUqoPodrFjBdMzv5wlN3VmHnoTMWGYPd+9YsmIrSkD+nhO2x1w7gvuuv9FQOEfHzuO/6K7Hpjzbykz70bvZCCuIWzKrOBua2Mejp99h7j6zqKMXEx3dANq1++jiCIz+ch5SkQFVhZG9zBPiroWF8elFzuBgzPAxRUiCpWhZ5QlDw2t6P8TfjL0PlyBKcbte2GTUsbCTS6Fn2uuziQlyAj+NRGvZhxctNWDarMmvbhKBg1faD2N50OquP5y4JiAZ5RILW7XUXgrV3Vzv2/WhLzHDbAIDbq0fjidunIBLsdOjw+3nDFYBwxHKuNt5Xg+l/XWY4hegleZ3OJwDHv7n18JYnA3asqpTiL6cvYlx51OJWcfXooa6cI5VS/P7IWUwfV5bl5uFW+5+0xTE8GjT6fyEuYGxZdMD3X6XU8R5ya3zKsoqk3Om2Efbx8PlyPp0XlFWdrp2nVOv4xFU7sOrWq1H72cuNedJpTJslEXFBc+RISmqWjEFVqeaSEeDRfFabw9beNRXHzsVRObIEhHgzz+T6rNDb1d9zy5RR+P7fXY1AumBMXzur9IN0Lq8G2Mozg1Ek5ApxRQI+lIR8SEkKCNG8l7/9ShMoNI/kiY/vwNc2NiAlqQDVVq5uuroCdfWHMWnVDjz66gFQaBnoMUHG0s2NFtnF74+cRVJS8cCWRs3VYs6krG3PtCdxISFqocuMPp66kMTDLzehPSnh1AVnmcmjrx6AogLferkJ1z/1Dh599QBiKRl19YeNB2dAcwo5HxOMPl5MyXhxzwks3dyItoSElGQ9V/dtbDDKe5eG/PD5uJzncyCHEwcKZrcK/TqMKA1BdGl13uzmMfHxHbj/xUZcM2qoa+1LkoKQ32fpf8jvg+RS+ylRMRxq9P5XjixFyoUxlBAV23vIrfGpqhQXkpLl3FxISkUjW1JVirggIyUqEGTFcLHYe7IdZztEy3EPjQSQyhgTZvlCacgPnuNsZQwcR0BBsejf38OcZ34PAGiNi8bc6SRB6+11zGf+0t8zfdwwKCosx9waF6Eoaq/6kC9OUpD+ls4VxMMzISRECPkTIWQ/IeQwIeRf0q9fSQh5jxDSTAh5mRAS6O++Mhj9RT4hLlWFEQa0CwnqoTvz+zKdAOyyzaePKzPer1L7bVUKBHycQ6gdJicO2JYW1mUmZqePp+6sspVd2ElDbqseYxyjqqLLc5XrfA7kcOJAwWu3Cq/bFx3aFwvALcTr8VnssqWEpIAnBCqlkBTN9nNdbTVW3DzRkFRYXYV6vi+zBObBGyvxsGnM2UnQ3LiO+YwP/T12bksDwVmlv8dgoaTGCgBmU0pjhBA/gD8QQnYAWAHgp5TSlwghzwL4OoAN/dlRBqO/yJXtbIS3gp0uHJnFRNriAgI+3shkNv9Nl144ZdmbXTVGDwvbvmfMcM3tYsXLnc4fuvRi9PAwdj58Azbs1txBvpV+z4SKEhxtiRnVDPW2JlSUoG7+tcbrv/7H6y0FIRo/ajPerzt/DAn7jX1Egtpx5jxXAR5hP4efL65BKMBnFZpwO7O82Chkt4q+aD8S9OH+L16ZVUTGDbcQL5wPzAxkFwQ3iAR4UEpB0hKGaIBHSlJwWWnQweGl58fN8xzKIgH8fHENgn7O4m7xs3easWbnB7ZFSXpDPuODUopogEfI4VpHgz6tuEs/zX39PQYLYuWZasTS//WnfyiA2QBeTb++CcDt/dA9BmPAYBficnLhaE8Ihrzi2680QZBVPJAOIZ/rEBylF3bhPrNjhZNbRiwlWyQZ33q5CYraKRupqz+MlXM0d5D6/adRV38YMSFbkqG3pb9e93fXZMkDrhk1FHV/d43F+cO8j5Sk5HWulmxuRFtCxIqXmwzJhx4WdDuzvNgoZLeKvmhfcpCduCUL8XJ8FrtsKSVqbjxxQUZCVNCWELFkc6Oje1BvjltVKeKijIQkozXWKdnQ5+nxl0Vxqj2Jr77wHpIurqrmGh96EZyvb2pwdBjRHZP6y2mov8dgQTw8AwAhhCeENAE4C2AXgGMA2iml+kz2CYAx/dU/BmOg4uTCEfT5wBOCNQuq8MTtU/DLxk9QN/9afPDEPIR8vKP0Yn1tNXavnIVjP7oFu1fOwoZF07H3ZJsRXnRyy/BxBGXRgK0rR+Y+zFndmUb96xZWIxrk8dw9M7DiSxNsw4ov/ekk7pg+Fs/UVkOlFCNKg3mFWe3O1SPbDmDZrMqiC017jZ8jeOHeGWj655vx4ZO3oOmfb8YL984oCLcKAAjk4azQGzyXhaQr3ak0/a+LDzfFLltSKMVDW5u0sZT+fURpECVBHusXVmccd8/cJxRFRUKQERdlXEhIiKWyC8889toBLP4/V3ZZHMVN9MhbeUkQdfOvRdPJC1i3MLcsztwvL8edmf4eg4Ui2wClVAFQTQgZBuBXAD6T77aEkKUAlgLAuHHjvOkgg9FLvBqnTuGtcIDHks0NWL2gCiEfh9unjcVjr2mlgj94Yp7tNqOGhtByScB3f3mwszztwmp8YcIIfHoxhae/UoVRw8IWaYZecOUnd2kFV9bs/MCQZDjJO568YwoCPIf/fO8jXExIeHbRDJSGtdD2xnePY/3bzca+h4T9WQVabp821lIWWi/dXb//dM4wq9O5qhzZWXylWELTvSGfserjOFxKZZdwLou4k5ri93EI+jhsWDQdQ8J+XEpKIOnX3YDnOEQCvKV9H0fAu+T35qUsxOuyxl7LQtyiJ3OqoqiIBn2YO7kCKtXkNRVDglhx8ySs3HYAFUOCePKOKRhXHkFCkBEJdH9VX1FUdAgyYoKMUUPDiJRp19xJEmeWrHk5/9iNm6furEJ5JGDM50lRc0wyRwPNhaf6qpx2f4/Bgll51qGUtgN4B8BMAMMIIfpMMxbAKYdtnqeU1lBKa0aMGNFHPWUwuodX49QpvNV8NmasrCYkxbIK7FSEJCbIWLltv3W1bGsT4oKCldsO4AtPv+NYcKX5bAzNZ2PG35xCoEdbYpi1ZjeWbdmL26rHYO1bR/HAlkajKMvat45m7NsaXrdb0daTDPV9OIX2cp2rrrYdTOQzVpOyfQnnpOxSiWhRwQNb9qL6B7sw/rtvoPoHu/DAlr2uXZ+krGDJ5kZL+0s2N7rWf0+LpPRBMlUhyJZ6Mqcm0kWjbqseAzntuvHwlzoTBbc3ncasNbvx1RfeAwV6dNwJSUF7QsIj2w6g+WwMHSkJH7flLu6k/9/L+ccpStmRls9d9b03cKo9aeuYlBD73v++P8dgQTw8E0JGpFecQQgJA7gZwF+gPUR/Jf22xQBe758eMhgDA7uQmZNp/8/eaQaQnfAHQEtUWTDV2GbFlybg2XtmYEjYj7r512L+1NHGe/Xtn793Bg7WfRmRAJ8V5tP3Zy6akqvQyfypo1E3/1oMCfvR9M83Y+7kCseVukiAt7hzOJXurhxZ0mVoz+5cZRZYKZbQtNf0RULf3MkVFlmIPk7can/VrZ/Bwbov48Mnb8HBui9j1a2fca39sEOhkbAL46svkqn6Kjzf10SDPkQCPIaE/ZrvfIDHuPKIkUB97Ee3YOfDN6BiSLDHYyEa9OHysgj+fKINP3unGSVBHy4rCWZJQtbVVmPnoTMWiUjYx7l+3vVr6TRuSoI+Y6zazduGC1EPx10hjqVCkW2MArCJEMJDe+B/hVL6/xFC3gfwEiHkCQD7APy8PzvJYPQnuUJm5vDWydaExb3is1eUGeW193zYarQX9BM8eccUjB0eRltcxAMOMgh9tbiu/jDW1Vaj8aM2HPj4Ip69ZwZKQ76s/VWOiBrOGOc6BDz9lSqMGR423gcAK788yZCQ6OF+Ie3NbO6jthquYPu+T4ywYkdKsn1fUlS0c5AjtJcVChQUcByw9u7qARuaHqjoK6uZ1yEuyCgN+XvdvigpmDd5FJZt2WsZJ6KkIBTo/UebbPKpNrcvSwoCLrSfkhQ0ftRmkYXsOXYeX5gwAiW9LEChR1Ayz31CVFBSALKQ/sTssy0pKgghkBUVK+dMwiPbOuek1QuqkBKVHrmjxAUtOVBfaW6La/ImsyTk3CUBbxw8gzmTR+HB2RMQF2UEOYK2hOTqeTdfy7r519rPnZKCskjnvJiSlE4HENO8GHO453ONu0IdSwWx8kwpPUApnUYpraKUTqaU/iD9+oeU0usopZWU0gWUUqGrthiMYiVXyEwPb4HCeGg1r6yay2v7OIIVN0/EP/5XE2at2Y1j5+K2iSxmr2U9oUX3fF771lE88GIjEoIMH08s+7tjxljICsWZ9iQkRcWjrx7Ai3tOIBLgca5DsJVdPPRSE2SVZq3UPXVnFfwcwR0zxhpZ6pv/eMJ2Rc/HIa/QniUUGPJpmsYBHJoeqHid0Oe1z7Pg0L7gUvscIZgydhiWbdmLiY/vwLItezFl7DBXKgAyn+eeo1Bq/FxISNj47nH4eM7R974nRPw8hkX8WL2gCitunmiMM7MkJCkpeOLXf0Fd/WGcupDExj8ch6hS18+7+VqaI4PmcRMN+ODzcca8qBfdypwXezLuCnUsFcrKM4PB6IJIgLd4M+seypEAr4Xk0qsDZRG/xRNZL69tTvIjpDN5xUkGkem1rL9eEupMfokEfVi1/ZAlebD5bAdm/HUZRg0LIy7I+MV9NQj4eUiSYvTLKdyfkhRjRVv3f36mthprfvWBZR87Dp0xVkYuJSW83nQK98y8wvHc5Vvm1aNysEVJwM/j/eOtWT7GN0wc6Ur7he7zHArwuHhetNyLJ1vjGD0s3Ou2mc9zzwmbzlMk4MOH5+NZsjag52NBVSmSsoohYT8CPAeVAlu+8TktB+XYecy86jIjMe9//3Uujp2LY81vPsAbB8/gmzdNcP2869ey7u+uwe3TxmBI2I/n7pmBqL6qHOC1OS/9AJxr/uvJuCvUsVQQK88MBqNrUpJi8W02l97WvTgVRUVbwlpW93xcxJl2a0lss7enU/JgPIcHs/77paRkaXfPsfO4ZtRQ2/Le5+Ja2VunRMKOlIzlW5twMaGV8Nb3nbmPOc/8Hm8eaoGsqkai15uHWhwTbfIt89rf5WALDS/LTwPF4fNsV76c+Tz3H7KsIibIiKd/zsc0v3unMtndHQvmOWTFy01p/+gGw9f5limjsPPQGUxatQNLNjfgdHsKP3un2ZDHOY3J3pz3hKjg3xZW45Ypo4woyP0vNqI1JuIXfziOSavexJJNDehISWiNC13Of90dd4U6ltjDM4NRJORbetvOx1il1pLYe46dz5kgsq62Ghfigm1Yfu/JNkMO8nrTKcu2TqVezeW97UKHurREl4yYvaRfbzpl2489x87nFTrMN2xYqOHF/kJxKD/d01B3Jl7LQoIO7QcLxOfZS/rbY9crkrLmgkEA8IQg7Nf87tfuOpI1J63rgb+zeQ6xm6MfeqkJcyaPspXH6X7Sbp/3iJ/H5yeMsB2L5r5cSEhYvrXJ9fmvUMcSk20wusUV3/l1t95/4se3etQTRiaRYKdsw8lD2SkUPXpYGP9z5KwRYk8ICtriKSOknBI7JRUdSRmyqmBsWRSxlGRskxQVqJTihokjMW1cGfwcwT0zr4BskmMkBAUVQ4JZ+zeHRfWVbN0L+tSFJAiA8pKgUV571LAwEoKMZ+6uxmWlQbQnBMMLOi7ICPt4fGHiSBz54TzH0tv665lyl+azMa2Ed0bYMFd40SyLYWh4LXvwWhbi8/MgKckiq0iJMnwufah7fX68lBj1t8euV2hOGz5QlYLjCUCBiiFBLJtVidHDQtiwaDpKQ34kRQXhANdtz++wqfy2WRqnY/aU1/8/oaJEk6Cly3Lr5z3s55AQFW1e7cX55zhiGYvzp47GgzdWGtKR+VNHo37/acMdJLO/vZVXFOpYYg/PLlDID5Td7Ttj4JISFSMj3ClrWpdjZL5+ISHimtFDjcIi735nNjiOszgNrF5QBY4QPLClEXs+bMXOh29AXf1h7Pmw1SiDbXbIWL2gCqUKD0GmlkIZqxdUQaWwuH1kZmnX7z+Ncx0Cnrm7GpQCK1+1tnumPYmV2w7gqTur8K2Xm1C//zRmji/HC4trDCeHknSxDD3L2ymruzTI22fSSwoiJlcFJwcD3WmkEDLE+5KEU+a9IKPEBbcNsyzEDQeETERJAQXJcttwy83DSzeSvnAwMJKQAVccPAYCKVEBRwBZpSAKAQVs5wY/z4GCR2ko/4dn/ZrU1R/Gn0+04a0VX7S9/pm+zpnjgeMIIn7e1eurj8URpcGseVx3VtJ9qL1wcCnEscRkGwxGkWAOk9tJH566swrb952ylUSE/bwlbCfKqm3IPSl1unKY5RxOpbY5jssKBz6y7QBW3Dwxq+SxXUnvaJB3LOGdHdbsWVa3pNrLCzJLeOfyy2YSjmw4Yn9N3XCTAADVQRaiuiQL8drNw0vZCZMY9QyFUkgqhaxSXEpK6EhKtmMs7Od7JNl4yCR7WLvriK0czuzrvK7WXhri9vWNpD3HV9w80bbA1IqbJ2J4xG9Tmnzgyyu8ojAe8RkMRpeYQ2+Z0gfdmUJ/3ewtqztRmKULhMDy//MdglYwIB2+tnPIqJt/rZHcAuSWiYwrj+DID+dZ9q+X7bY4hTi0qzsSGGHNLvybAWfZRTRdfjdLtpFRwjvTqeRSUsL2faf6rHRuoREK8PhtY4vtWHODiFPRnAJx2/BSdhIJ8Jg7uSLr3LtdJKXYnGfM11Zf7Z07uQI/X1wDhVJNtpbSionw3fTizpx/6vefBkdguALFBc3H+WufvxLfvGkC4umiJUlJRYQQ49yqKnXVoUJ3/yiLBnBZKXGcr5H+zpgprwBgFFgplnGQD+zhuQAoZFlIdxlMx+o2mWFgXfrw/L0zLPKK2Z+psBSWWL2gCqKkWMKT735ntm24ctX2Q2i5pCUKpjpSCPl9FklGZvGUXKHpKXW/AQDN+3n6WMMxw04Cktnu6fak0VZCUAx7vFw4Fo4Q5LxkG6pKswoUPHVnFfaebDf65VYRimIgJSq46ersseaWrMLrIixet++l7MTrAjKFWtiiK3T3DEWlUFWKUIDHndPHIibIlnluXW01yqOBbj1A280/LZcEnGpPYuehM6i9bhyWpgulZM5H+rkFgNa46Dg2uzv/ZF7H/3n0Roc5snOONcsrinUc5AOTbTAYRYIeessq9+vrlBs4ySsypQtOso1lsyqN8PXwaDBn8ZTVC6rAO4TuVZVa+sgRGH2362NmuxxB5+95zmJOsou4oOQl27ALlXZHNjLY8FpW4bUbhtPY5V2SnXjpRuK15KRYZSE8IfBzBD6OwO/jICmahMPuXHb3WHPJvuZMHmXsI5dTkn7e7dw/ejL/ZF5HlVJ7qZXDHFus4yAf2BIJg1Ek8DyH8mjA4g4Q8fPG63q4LR8XjtHDwjkzwXNJMiZUlOD5e2eAJwShAJ9VwEQvknLkh/MQF2QEOAK/n8erjZ8YYWY7GYVRlGXnB1h7d7Xl91yYw8ulQT5LdnHPzCscwv/5uW3kKxsZbESCPtz/xSuzZAluySp8fh7nzsWyioxcVjrUlfbtxm4+4y1fvJSFeC05KdTCFl0R8HEgBPBRWO7l3pxL8/wTDWTPPwAwZljYKJRy1YhoznP75xNtkNNfgvSxmRSVvBcRzJgLpHxlxlhEgj5LsSzzmFcpzZJlFOs4yAf28MzwFK/dPJjMwwrPcyhNhxIzM7RLgtoDjFMo2vy6XhjFKRO8K0nGxXSiTd38aw05BgDU/d01uGXKqCwHA16U8eahFny//n0c/pc5tjKKpKhgzjO/x8zx5TjaEjN+zyXbMIcV7cKhT91ZhdPtybxCoI6yDybVsEWSFFwzaqhFlrCuthqSpCDoklvFE7/+X8v1mDm+HM/fO8M12YZ57OrtF4IsxGvJSTHeC7KsQlS0nwDPQaYUoFoEpafn0k7WsHpBFf4pLX9bX1uNm6/5KyzZ3GD8/ZnaaiyfXYm1bx217E8vGqL3pX7/acNlqG7+tT1y/NELpMy86jK0JyWcj4m2Y/5kawJfWvu7LFlGMY6DfCHUpRBaoVBTU0MbGhpyvqfQ7du684BY6MfaXfI8N/2+fJjPOLXDksQjaKsRIX9nIkdKVtAWF7MeTC+LBnDe9Pry2ZWo/dw4PLTVajG3ZucHnZpnSc7SPK+rrcbQkA/3bWywtbBrWPUlLNuy1/aBhyMEskrBE2DJ5sas97xw7wx0pGSUhv0I+3mcjwkI+3mUhLSy3aqqeV2bV0digoz/+J8PMWfyKEyoKMHJ1gTW7jpiJPnNHF+Ony+ugaioaE9IuLwsgo/bEhge8aM05Ld8CPVW3+dRgtWAHasdKa2SpVcPt4IoIylbr9uwiB9hH+fKw7koymhPZWtdh4V8CLjQfkKQ0Z6U8O1X9hvt/+SuqRgW9vd6dT4hyGhLZN/nZZGAKyv/PbwX+nWsdjWndqQkcISAQJPUxAUJw8IByKq24pqv5tl8n8cF2XIPzJ86Gitunohx5REcbYlhSMiHFa/sz7pHnrtnhvVL58JqDAn6oFIgLmqVVs0LAHoyuG7Xme+Dq6pSxEUZrTER3/3lQYwoDeJfb7sWFDASTQkBfrX3lFE2/OO2BP5qSBAy1XyrW+Oi5XOiCDTPeXW8uL8aMBiDCKdVDv2Bd/3CaSiL+i2uFuawXKbbBU8InrxjCi4vi6AtLiAS8GHt3dW4lJTAcwTlJQHEBdkIy8cFGc1nO1A+drij6wfgHAI93Z7EI9sOYMs3Pmf7nnDAhyWbG7F6QRVe+0sLbrq6Ag93kWAT9nO4fdpYx+TDP59oQ8DHoT0p4bu/PGjaPjs03xsz/8GYWOO1dIDnOIiKbLlu6xZWo8SFB1sA4DgOkQBvcazwcQRcT+LjNgT9HPxC5z32cVsCfo4g6O99+15LTgq1sEUuIgEeSVFBXFJQFg4gKSr42sYGzJ1cgQUzLu8sEpWSEXVw28i8zz94Yp6l+EhmIvR/LrGf60qCPjx7zwyUBH1oPhtDWSSATy+l8Mi2A6gYEsSTd0zBuPIITl1IYvXOD3rs+KMXSIkEtHt11a1XQ5DVrC8K/3faGDyQkXz60p9OYv3bzVg+u7KzuFYRjIN8YQ/PRchgW01maJiTNwAYCUh186/FnGd+j+Vb9+H5e2c4hqLNr+98+AasTCetmN+nt6WvIN7/4t6sgilN/3yzrevHhkXTAcCYmC+CAAAgAElEQVQ2zBdLyUaSTC7JiH5MGxZNN1awdz58g7GtftzLt+7DC4trQCk1kg/1vz32mnZOdIeMmCDj26bVH237JtsVnJ6a+dtdG72PxRre9Fo6kJQ7fXMB7Zw+tLVJW9n29f4BNCkrzivnLrSfEBUsf6nJYWW+d+0nRMX2PncznF6IhS1ykRAVKCo1xpCewLfnw1Z8v/59izzi+XtnGPI4SxsZ97l5LjMnQgPaeD3Zal945OhZrfCSvr8Ni6Zb5rjtTdoq85N3TDEenPVtu3uN44K28vzZK8pw+7Qxlsignhy5YdH0rNfq5l+LtW8dxdq3jmLPh21FPZfZwdw2GIwiwSl5o3JkCeZPHY26+dciGvThuXtmYMWXJsDHEaz40gQ8d8+MrNcrR9qX985MGNTdDszvLwn6bAu0lAR92HPsvMUhQd9/SUjzc54/dbRjgZefvdNs7HtI2G/sz6mvkQDvuPpZObLEaLc05Hfc3i26SqxRVYqYIEOl6X9dckXoT8J+bdV298pZOPajW7B75SxsWDQd4QIpb232/z72o1uw8+EbUDEkWBDt2zk7MDeY3ESDPmNeySxXvfPhG7DlG5/DmGHhnGM48z43z2V289Qzbx3JKjyiz3X6PLV+YbXjHDWuPNLra6wnMq5eUIXS9Dysj8f5U0cb863+f33fmWXEi3kus2PwfE1gMIocp+SNTy8ms8KF62qr8Q+zKtGWELO0dQ/OrkRCtF81zEwY5Dkt7Jw07fvYuTh2HjpjCRlv3/cJ/v7zV+LzE0YgwBFsWDQdpSEfWuPW/ev6vTW/+cAITZ5sTVgKvOgr1fr+HBP+0p6tdn9LigqevGMK1vzmAzx4Y6XnSS+5EmvcLrU7UBBlFSlJtcgqfnp3NQK8Cl83C0zY0Rflv239v13yqfay/WKUVXhNSlQgU4rlsytzlqv+6d3VCPjsx3DmfV6//zQqR0SxYdF0yxyp03JJQDTow/P3zkAkoEk0zPrlhCgjGvQ5l8YWlF5dY1WliAsKtv7pJO67/gpL+XB9Pq4cEcWlpIS6+sOG5O1ch5BVRryY5zI72Mozg1Ek2K02rV5QBZUiyzf5oZeaEBPlbP/SrU1ISqqjx+2G3c3G6khKUvDN/9qHWWt243u/OmissGzY3Yw7ZoxFXf1hTFq1A3X1h3HHjLFGWeb7Njag+ge7tCScrfY+0ec6BEQCPARJgY8nONchZJV41vvHETiWgXYuEa2tNJ3rECxlxr1apcu1ElisXqkKpfjWy9br+62Xm1zxMQYKv/y3lz7PQKesgiPpf4vs4cVtFErx7tFzuO/6K0EpdSxX/a2Xm7I84HXs7vPa68Zh8x9PYNX2g7bzTMinlfpujQmoqz+MNw6esZTmDvl4DI/4bbatRiTA9+oaJyQFG989jtunjYVKYTsf33f9ldi+75SlVHdmGfFin8vsYCvPDEaB4+RjHBdk+DmCgN9eMmCWPphf1506ms92GMlSHUkZsqpg7d3VuJhOnIoGfXh20QzIqoJhkSBOtyexZkEVRg0L40x7Ek9/pQqjh4WzkpX0febyiX7unhkAKIJ+3jHBkSMBQ/Lh5E0KwDFxKuTnjVWblKQYZXK9WKXLtRJYrF6pXssqvE6KK/Ty38VYPttLokEf/nFrE478cB4oBSJ+6liuOtMDXsfuPg/7OPz9F8ZnzTN6+e24qP07NOSzzN1hX2dSYmnID7+P65yjBO26mkt29+RaRwI81r/djOZzcTxTW+2YvFj33+8b/x9XHgFVKf7+C+PxzZsmDIq5zA728MxgFDBd+RivXzgNYdVeunApKdm+fq5DwMt/Oona68ZllVaOSgokWcU/ZGRjb/l/J/DmoRYj7GyXbBjPkFE4JZQdbdGSZVYvqAKlxDbxqSMloyMlGcmDTkmQAHJ69eqyDHMZbq+SXpwSrIrVK7Uvymd76cPstSzEy/MzGN1deoMsq0hICrY98DdIiopmTyfIEGS12/em3X1ekn4IjgTSJa1jGdemthqSSi22hebrpT2YmuYok699b661PvfU7z+NH9x2rWPyot2x68c0GOYyOwpCtkEIuZwQ8g4h5H1CyGFCyEPp18sIIbsIIUfT/w7v774yGH2JOUzmVNaV42BbFnb7vlNZiXmrF1QhGuAt5WIzy3jblaq9rXqMJexsVzbZzxFLCXG/TXllPVlGb0tWFce29GPdvu+U7Xsift52H/r2A4ViTe7yurx1wOHaBly6tl7LQrzs/2AKn7tBUtbkC5UjS3EpKWHTu8dRGvajJMRnjYF1C6t7dW/aXZu4qBiOP929Xr251ua55/Um+3nUKs/IfezFOpfZUShfBWQA36aU7iWElAJoJITsAnAfgN9SSn9MCPkOgO8AeKwf+8lg9CnmMJmT60QorZvTQ4lHWzqTUvaebDc8mI+2dIa9J1TYt+UUah4S9lve0/hRW2dZ5nQJ7oBfC1WWRbQS4gE/j6Cs4ueLaxAK8Ea5WrNn6bBIEC/uOWHIRxKCApVShNL+u9v3nULdf7+PK8ojFr9pPeRJOIL3j7da/iarFAE/j1i6fHl/r8QVa3KX17IKfx+U5/5tY4vF5/n1Jq2cuxt42f++CJ8rirZaq/c94rf3Pi4EokEf1r/djG/eNAFhv7Z4EAnwWPWrg3hkziT84r4aSCo1jlUrLtez+9Pu2lxeFnG8XnZlsbtqT982nzku7Ofxn0s+h4SgwM/BMh4DHMHXPn8lvnnTBEMGmItincvsKIiRTik9Qyndm/69A8BfAIwBcBuATem3bQJwe//0kMHoH/QwGdDpKWpGD5npocSEqKCu/rDxgFq//zTq6g8b5a5bLgm4lJQM/9HMtvRQc+brl5KS8XtKVFA5shT3v9iIiY/vwP2bG3E+LmLFy034xR+Ooy0hYulm7W8PbNmLtoT2t2Vb9mL2ZyoMOyTd3aPuv9/Hsi17cTEhISHKRrvLtuzFLVNGYeN9NRg/onN/Szc34kJSgqpSpCRrX5ZubkRckLHi5SYs2dSA1rg4IKyUijG5yyyruOp7bxjjS5fT9JaUqGBoJGCMpaWbGzE0EkBKdGd1NSUquOnqCizbstcYbzddXeFe+5JD/11YHTbPCzrmEs+9RVFUtMZFS99b4yIUxSGTboATF2T828JqJEWtAqs+J7ZcErDr/RZcSsmuHKuqUsMpSGf+1NGIOcyrJ1sTmPj4jpxzVUKwv9ZHW2I5t9PlHks2N2j72NyAS4KCaECbh6IBHy4J1uM+HxfRkZJyzpnFOJfZURAPz2YIIVcAmAbgPQAVlNIz6T99CqCin7rFYPQL5jBZPq4RTo4cuovGutpqbN93Cmt3HckOV9ZW40JcsA3tvd50ymhLVu1dBJbNqnSUgyybVWlx28js1+oFVfDxxFYyMv2vy7Iy4vWwparCsS8slO0tXssqvHar8Nptw2lsOjk5dAevw+cJSbG9Fwv1XvJzBJ+fMAKXkpJxXLpH8+3Txrh2rLq7hVkut+LmidiU8Zp+r6zddaRLKQbHZbsNmeVvTtt1JffQ/p49V19ISAV7nd2kUGQbAABCSAmA1wA8TCm9REzaM0opJYTYzmqEkKUAlgLAuHHj+qKrDEa36ck4zQyTpUTFEnbjCQEIkBBlqCoQCfIYYuPIoZfd1mUQADDjr4dZ3ufjCC4rDUKWlKzX75l5BRbMuBySSlES8uGFe2cgLii4rDSI5rMxbNjdbCmwYiaz+MqEihI8/ZUqEAA/uasan15MQqXO7gQlIQdXhHSI2snRY+fDN2DD7uacoWzmWGBPPmPV7+dBUpJlrKREGX4Xi6SsuvUzGFcetcge3HKriJiKmOiykw27m11z24gEeYf2e39+vA6fRx3OjVvn3i3ynVMDfh4BwChTPX/qaDx4YyVGDwuBEFikRz97pxlvHDzT7WNVVWpxt9DajCIpqnhw9gR8ejGJZ+6uxoghQSQEBZmXqmJIEKDal7qUqEChmoxEVYHf/qXFKr/7Te6S3Xpf9GN9bO4klEcDkNKvJ9JOIHZz5+VlERCCASN76y8G1kjPASHED+3B+T8ppb9Mv9xCCBlFKT1DCBkF4KzdtpTS5wE8DwA1NTX9H6NlMGzo6TjVw2SKoiImaN7NZucN8+9zJ1dgXnr11+yWUUJhKcs6f+po3HR1BZZu7ixgsnpBFZrPduCaUUOz9mFu1871Y/WCKlxKSkZ4MlfxlZgg49FXtRW5+VNHG0UK6ubbZ4M7tZkQFOP3zL+dupA0HD1SkmLJZNdhjgXO5DNWJUkBBbGMoXW11ZAkBUGb891dZEnBiNJQVvuypCDgQvueF0mRHNp3GI/dxcvy2V6fG7fId06VJQUyBWRVK5Jy+7SxeOw1be783q1X2xYO6Y4rij6X6LI3/cH28VuvxsPpuXj57ErUXjcOX33hPcu+dFbOmYQlmxsc59en39QKPtXVH87pdmHuy/LZlVh43TgE/BwupayfHXIHtZ07P25LQJBV1NUfHtTzYUHINoi2xPxzAH+hlK41/akewOL074sBvN7XfWMwBgrmUKrZecP8+23V9iFIhVJL6G/FzRNtQ8rTx5XZ7sPcrp3rxyPbDsDHEwR8XM7iK+tqq0HVzr48eGOlIcmwK9utywDsXEM4zj6kqRdJ6SpMzhwLeofo4MwiuqQxFxzaF1xq33NZiIeyDa/xWtLS1wgqhUIpkpKC+66/0phzls2qdCwc0h0JjD6XrN11xJirHryxEg+bxq+dpE2XsZnnY6f5dcXNE/OS7pn7svj/XIm4qIBSZM3f5r5mujF1JQkZDAycr4i5uR7APQAOEkKa0q99D8CPAbxCCPk6gI8A3NVP/WMw+gwnKYE5lDqhogR186/Fz95ptrhwZBZG0cOT0aAPlMIw4Qfs5Q5miUTlyBJjf0PCfsu+nZw6okGfxT0jlpLBpWUjeiJZNJ1kortw6G3pqzV6eDKWkrH3ZBtumDgSb/+v1RWh6eMLqPnrckSCPAhgW7Cl6Z9vxutNp9KFUTplLam0VjoS7B/D/2KRikSDPtz/xSs7XVfS18ut0L7XRUa8bt9L2Qbg7TjyuoBMX6Nf07CPB8cTQ87gNJeVhLTk6whHbM+toqgQZBUq1a4zpRQvfv06xEUFQZ4Y86y57atGRG3lIRMqrHI3J1elceURrL27usuCT7ocQ1Ypfnp3NUpCPlBKjflTb09OfwnV+5QUFVxMivjXX/8lpyRksFAQK8+U0j9QSgmltIpSWp3+eYNS2kopvYlSOoFS+iVKaVvXrTEYhYuRIb2pISsLWw+l1tUfxsTHtbLYK788CZ9eTBrZ2HphFACGJEJ///0vNqI9qTlftFxM2WZwmzPFP72YNPZ3pr3z96Mt9q4fR1tiONchGA4GK15uwqWUZBzL0s2NuJiUsOLlJizd3Ii2hIhTF5KWtszuIPe/2IjKkaVIiQpmf6bTFWHzH0/gmlFDjSzyldsOgFLgWy83GY4PR1tiWLZlL+ZNHoW4IKMtnXW+4uUm43en43DLscCOXNe30JAkBdeMGtrpuvJiI64ZNRSSSytVTs4vbrl5eN2++X7Vy9ivnDPJFTcPr8eR124efU1KVCBKCmKijFhKkzOs/PKknPOg07lVFBUdgoy2RKeTxdLNjTjdnsKmd4/jfFzEqu0HLY5G86eORmva5cMYC1+ehOWzKxFLyZb35nRVIloxlZKQs9uF+dqdbk/iUkpCW1w05k/zvur3n8acZ36PRf/+HmRVxcptB4wHZ/N+ByMF8fDMYDA0ckkJ7EKpj712ACrtlC6YjfDNkohMJwo1Q8ahh+z2nmwztldpZ9jZ/LudvELP/hZltcvwo+6E8ci2A+AIHNsyF24xH0eu8Gfm9g+9pAWy7PpkdxxeG/4Xk1TEa9mG1wVwCtktxOtxVGzFMFRKIakU7QkJSUnB4rR0w2keTEpKTpeK9oRkOxfPmTzKmOPW7jpimYsftpmz7rv+Smx89zjW7jqCNQum5u2qlAvzteMI4OOsLkZOTkt2RbUK+Zr3lsKMsTAYg5Suih/Y/W3M8LAllGd25MjlfPHtV5oMicS5DgHRAI8bJo5ESlTw7D0zUGqScIweFnaUV5izv396d3WX4Uez88ZfDQ3jWy835cwkL81w23BqV5eyZG5vPg/mbTOPoy8kFH1R3KKv8Fr2EPDz2NHwsadFTMwFdswyITfw8vx4PY6KrRiGLjcxJ2rq848+D5oL/fzkLmuhH/O5jQZ9hmtH5nv0+aVyZAnq95/G2rumGvOLkzxk/dvNhoTi6a9UafO5aQ7v7rnPvHb6vnTq958GRzQJXzjAo/lsDGXRAOr++32jqJYu44gECvea9xa28sxgFBC5wqW5/qaH8hKigq9vasCUut84hqWbz8bQfDZmFLg42hLDwy81YXLdbzD+u2/gmu/vxAMvNlq2zwwl6vKKWEq2FGUxv88p/Gh23mg+GzPaigvWtvT3ZBYdcGrXaft8jkPPVvf6g6KYwuF9Iat481ALqn+wC+O/+waqf7ALbx5qcbX95353HFX/oo37qn/5DZ773fGCkIX0xTgqpmIYcUFGXJDxcVvC+NHnH7tCPx+3JSzbm8+t3o7T3Gae4z5Ju/44ScTMY6R+/2l84el38NUX3oMKoDTk7/G5NxfNMkv5dFouCZBVFVd97w3U1R/GJxeSRh90GQcICvqa9xb28MxgFBC5wqX5hFLN7znZGs8KS+vOFzsPnTH+ZhcmXL2gylIwxe4962qrsfdkm+X1fNo1F0Yxu3AQUNsweq59mNu1O951tdU42Ro3tu9tSNTL61tohH287fkO+9w5lkJvP+K3b9+Na11M46gvCPt4BDmCYRE/SkI8SkI8Vi+ows5DZ2ykCtUYHvE7ntuIn8ewiN+2cMnOQ2cs81ppyIef3DXVYT/TPL+OET8Pn4M8SS989ZO7pmJYjuMdrBBaoNYyPaWmpoY2NDTkfM8V3/l1H/WG0dec+PGt+byt379O5xqnubLo88mwN79HlhQIKrUUVQmltw3xHJKygmjQh5SoaaojQR8Sggwu/T7z9mbjfr34SsDPZ70e9vGWds1/M/Zv2kdckBHkCHx+HqKkQFK7tw9zu5KkQDRtH+AI/H6rw4b59/4IR3fTJWFAj1VZVi3XIezj4fO5t2ZT6O0rioqE1Nl+xM+D591pfwC6tvTrzrv67JdlFaqqQjY9EqkUCAc4JETFIpEAkPPcZrptxNNFRxKiYsxF+muCrEJV7ffDccTz66iqFKJsP68mBAUcBwR5DklZHUhjyUvyOjCmeWYwCoxcxQ/yKYxgfk8g4EMg/brZ8F//e2n6QcFsQVViep95e/N7zG3ZvW7XrmX/pt/Nr4cCPoS6uQ/z+4IBH4J225u0jubf3S4ukQ9eFrfoa3w+zvY6sPY1eJ5DKe9N+8U0jvoC7UsRZ8xnZkpD2jUyn8dc55bnOURMX4KMOSmU/VokYH4tez9eX0eOI47zaknIdLx8dt8GM0y2wWAwGAwGg8Fg5Al7eGYwGAwGg8FgMPKEPTwzGAwGg8FgMBh5wh6eGQwGg8FgMBiMPBl0bhuEkHMAPurBppcBOO9yd/oTdjzOnKeUznWprR7Ri3HaHYptDHSHYjn2QhmrhX6+C7n/A6Xv/TpW8xinA+U8ZcL61T1626+8xumge3juKYSQBkppTX/3wy3Y8TAG8zkbzMfeHxT6+S7k/hdy3/uSgXqeWL+6R1/1i8k2GAwGg8FgMBiMPGEPzwwGg8FgMBgMRp6wh+f8eb6/O+Ay7HgYg/mcDeZj7w8K/XwXcv8Lue99yUA9T6xf3aNP+sU0zwwGg8FgMBgMRp6wlWcGg8FgMBgMBiNP2MMzg8FgMBgMBoORJ+zhmcFgMBgMBoPByBP28MxgMBgMBoPBYOQJe3hmMBgMBoPBYDDyhD08MxgMBoPBYDAYecIenhkMBoPBYDAYjDxhD88MBoPBYDAYDEaesIdnBoPBYDAYDAYjT9jDM4PBYDAYDAaDkSfs4ZnBYDAYDAaDwcgT9vDMYDAYDAaDwWDkCXt4ZjAYDAaDwWAw8oQ9PDMYDAaDwWAwGHnCHp4ZDAaDwWAwGIw8GXQPz3PnzqUA2A/7yfXT77Bxyn7y/Ol32FhlP3n+9CtsnLKfPH/yYtA9PJ8/f76/u8BgdAkbp4xCgY1VRiHAxinDTQbdwzODwWAwGAwGg9FT2MMzg8FgMBgMBoORJ+zhmcFgMBgMBoPByBP28MxgMBgMBoPBYOQJe3hmMBgMBoPBYDDyhD08m1BVipggQ6Xpf9W8XUsYDAaDkQGbUxmFAhurjO7g6+8ODBRUlaI1LmL51n3484k2fPaKMqxfOA3l0QA4jvR39xgMBqOgYHMqo1BgY5XRXdjKc5qEpGD51n3Y82ErZJViz4etWL51HxKS0t9dYzAYjIKDzamMQoGNVUZ3YQ/PaSIBHn8+0WZ57c8n2hAJ8FnvZeEdBoPByE135tSewuZihhv0xVgdLAyWe5I9PKdJiAo+e0WZ5bXPXlGGhGj95qmHd5ZsasDEx3dgyaYGtMbFoh0gDAaD0RPynVN7CpuLGW7h9VgdLAyme5I9PKeJ+HmsXzgNM8eXw8cRzBxfjvULpyHit37zZOEdBoPB6Jp859SewuZihlt4PVYHC4PpnmQJg2k4jqA8GsALi2sQCfBIiAoifj4rWYCFdxgMBqNr8p1Tewqbixlu4fVYHSwMpnuSrTyb4DiCkqAPHEn/a3PjsPAOg8Fg5Ec+c2pPYXMxw028HKuDhcF0T7KH527CwjsMBoPR/7C5mMEYWAyme5LJNroJC+8wGAxG/8PmYgZjYDGY7smCWXkmhJwghBwkhDQRQhrSr5URQnYRQo6m/x3eF30xh3cifh4JSSl6WxYGg8FgMIqdwWK15hWDRf5SMA/PaW6klFZTSmvS//8OgN9SSicA+G36/33GYLJlYTAYjIEEm38ZbsPGFCNfCu3hOZPbAGxK/74JwO19ufPBZMvCYDAYAwk2/zLcho0pRr4U0sMzBfAbQkgjIWRp+rUKSumZ9O+fAqiw25AQspQQ0kAIaTh37pxrHRpMtiwM7/FqnDIYbjMQxiqbfxld0d1xysYUI18K6eH585TS6QDmAXiQEHKD+Y+UUgrtATsLSunzlNIaSmnNiBEjXOvQYLJlGQgUuxbNq3HKYLhNvmPVy3uWzb+MrujunOrWmCr2zypGAT08U0pPpf89C+BXAK4D0EIIGQUA6X/P9mWfBpMtS3/DtGgMRmHh9T3L5l+G27gxpthn1eCAaAu2AxtCSBQARyntSP++C8APANwEoJVS+mNCyHcAlFFKH83VVk1NDW1oaHCtb6pKkZCUordl6W9igowlmxqw58NW47WZ48vxwuIalARdd1zs9wvo9jhlFC0Ddqz2xT3L5t+Col8vTL5zam/HVB9/VjHcJ6+LXShXsgLArwghgNbn/6KUvkkI+TOAVwghXwfwEYC7+rpjui0LgKK/Mfrzg4pp0RiMwqIv7lmv51/2cD746MmYMo8TUKBiSNDyd/ZZVXwUxNMepfRDAFNtXm+FtvrM8Bg9FLV86z78+UQbPntFGdYvnIbyaKBPPkx0LZr527yuRSv2Ly0MRiFS6Pdsf895jMLAbpysXlAFlQL1+08DKKxxz8iPgtE8M/qX/rbwYfpGBqOwKPR7tr/nPEZhYDdOHtl2ACtunliQ456RH+xrECMv+ls2MZjKfjIYxUCh37P9PecxCgOncTKuPIIjP5xXcOOekR/s4bnI8Eqj5xiCFRSAIK/92PUNQN79HUz6cgaD0TWKoiIhKYgGfYgLMiJ+HjzvTkA1ISpYPrsScyaPQuXIEjSfjWHnoTMs/M4wUFWKuCg7fjaWhHyDeqwMlJwBL/rBZBtFhJcWOXYh2NULqrBq+8G89mPfNwEdKYlZ+jAYRYjXll2KoqI1LmLp5kZMfHwHlm5uRGtchKKorrQf9nGovW4c6uoPY9KqHairP4za68Yh7GMfm4zO8f2LPxzHU3dWZX02Kqo6qD/LBopln1f9YLNAEeGlRs8cgj3yw3l48o4pePrND7C96XRe+7HvWxMuJCSmKWQwihCvNcMJScFDLzVZ2n/opSbX2k/Kqm37Sdmdh3NGYaOP77VvHcWa33yAuvnX4oMn5mHDoul4+s0P8MCWvYP6s2yg5Ax41Y/BG0/oI3oTLujutpEAj4ohQex8+AYjzLhhd3O3NHq59qnLJlRK8aW1v4Ns+uaWqQXMbCfs52z7NnZ4uFf9ZTAYAxOvNcPRoA9zJ1dgw6LpGBL241JSwutNpxB1KUzeF5rngRLW7gmF3PeuMB9bSlKgqkAkmP4s83FIyioiAR5186/Fz95pNlw1HryxEhMqSvDY3ElQKRD2c+hISYgGfUV3jrpioOQMeNUP9vDsIb2xOurJtilJwco5k/DItgMWy5yUpCAS6PpS57vPriyo7NrZsGg6Hp37GXz7lf3Gaz+5aypigoy6+sM96i+DwRi4JATnPImSUO/vb1FSMG/yKCzbsteYP9bVVkOUFIRcmD8SgpOWVUZJyN/r9gvZCq+Q+94V5mOrGBK0fKYun12J2uvG4aGXmozjfurOKkwfNwyzP1OBx147YGzzq72f4PZpY/HYaweK7hzlg9f3f9798Mgyk8k2PKQ34YKebKuqwCPbDmRZ5qh5Rhnz3WdXFlR27bQnJHz7lf2W1779yn60Z8g2utNfBoMxcOE4YPWCbC0o59KnjqRSW1mF5JKmkiPEvv/EnQefgRLW7gmF3PeuMB/bslmVls/UOZNHZY25x147gNunjcFjrx2wbDNn8ijjtWI7R/ng9f2fL15ZZrLlPQ8wh3z0sA6ghXQqR5YgKSpQVdqlBKO7oYZI0GGbII+YIHcZXst3nxxHUBbx4/l7Z1iy3PU27dq5vCxi2/blZRHb/jIYjMIm5OexZqemBdVlWWt2foC1d1e70n406LOVgu50JxcAACAASURBVLkl2wgFeKz5lXf9Hyhh7Z5QyH3vCvOxVY4ssRxn5v8B7biHhP3Y8o3PoflszHiP03uL4RyZcZLveH3/54tXlpns4dll7MJZaxZMRYAnWG4K9XQVvulJqMFpm1hKxv0vNna573z3qaoUbQnJMWRn187HbQnbtj9uS1j6wCoxMRjFQUJU0HJJwJxnfm+8NnN8uWv3d0p0kKmJCiIutB8XZNv+xwUZpS7INgq5AmMh970r9GMbURpELGWV7jSfjdked8vFFL7w9Dv47BVleHbRDHz2ijLH9xbDOdLJJd9JSN7e/93BC5tbJttwGbtw1spt+xEXlW6Fb3oSarDbZt3Camx893he+853n12F7OzaGR7xY/3C6oy2qzE84i/YCmQMBsMZrysMqpTay9SoO7INP0ewrtY6Z62rrYbfJb1qIVdgLOS+d4V+bCtunohNf7Ta0O08dCZrTGiluKkxBjf98TjW1VZj56EzWRZ2xXKOdHI9CxTzGAEAQl2aaAqFmpoa2tDQ4Fn7KqWY+PgOixOFjyP44Il5uOp7b1heO/LDeTn1cz3JZrZzuZi06s2s/jjtO599Oh2juc18C6LYvTYAkin6vQNej1NG0TCgx6qXjgz5zEO9bf/FPSdwW/UYi5vHPTOvcE33XMiOFT3oe78eWHfmVFWlAAEmPr4Dt0wZZUgum8/GcNVlURw7H7dIhX5yV7Xx+a593s9FUlQRDnBIiErRum10dQ8W6PjOq4PFETtwmd5ccKdwVlfyBKeHze6SGZ6IOWWMO4RO8glv5BOyo5RC/2Km/05sPnDcCqcU6E3KYBQ1qmqdB7rK9egOXlcAjAsy3jzUgu/Xv2+8NnP8/8/eu8dHUd/7/6/PzOx9EwIhxASNXBKoEskKqEWsFRQDtqW2ioQeBHpB5ehBiijHatsca/VYEEWPP6yeqiDniFJapadSil+1FaQXguFmK4SLYKABEkL2OvffH7OfyczOzCbgbrKh+3488kiys/O5zey8Pzuf1zxfxfjmmAszItvo63E+O74yDNFz54adx3QU3fhhxXj8m5dZpAjH2uO69v5oWwxikgVOCAEBSRKk+n5uSs2zUJF2LnBenyO93YBci8/rRmO/VJFenpBN971sLJ10Vaad81eYl9Aa5bPiNpQrTkb5yEc+OkOSFLTFzNeBtpgAKUMmI9l2APRxrK1sw8dlSHaSv27ldPg4BitSpIZP3laDopRcvmJmCD43o5+HGxqb0ZGQMG918riu3o62qIBFrzf26WNsd77KimIjxzx/pBnpIi/bSIkIL2Hequ2mb1LjhxXjxTnjuv3NqbuSBfrt06nOx795Ga5b9v45tyNdez7vN990ZYYTIu5Y3WDqz/uLr8ODv9r9ucbVKTJxzFKi128L5GUb+ehm5Oy5ancdGD+sGC/MHpuRO7dZ+Nxbyt/f0oHhJQUIejlEEhIOnAyjqrQwY+Vns/05GH1GtgFoxyfKS4gLMi4a4EfTiQiee68JlSUBfPuaoboUgwHwXcNx3LTwWtRv2Gs5rvXTRqH26T/22WPsdL7+Yu44KCrOizvrycjLNs42FEXNCILHaanCafnCyRnQFuOWxsXP6aQ9l6WTLr8AJB8IYAixlBnwcN1G1XU1rt3p4/mMTcpHPvpq2F0H/nq4LaMOgJ/XUbWr8nd9dgZDBwYBaPrOXZ+dQc1F/TNWfv66lTthyTVuFj4Xi5EPd+qen5oRQtOJiDkvEpjOQ0Jge1wrBwX1v/viMXY6X73JeQBgnV+cz3LKvGwjGXRJ4kirhlQzBtXwZCuoM6Bx+XFx7UicivCO7cjmkp9d2eGE2G3ZRTSpFTMGRdU59ae77bCrkzoZWcrm/zlg9PnIRy6G3XXgiiEDEOWljJTvdN1MZMiEwuhgOOKhjZi/ZgemVpdByFD5+etW7oRdrokkJBxti2HBpEosvtF8np2KCHjpg4NojQoQUs5DpzlEJCFhWk151ucT2Qr6rJMx0vXlfJcl5SfPyaDIleWb9/U4XsbJGdDnYs/KxS9T7kV2ZZ+OiVjwWmO3kXepWsEiW1Rd+nHtbh9zxckoH/nIR2d4HFBvnkzRNj6no2pXkXUHw/x1K2fCLte8svUQivwuzJkw1OIUuHBtI2qry7DgtY8gKmZk4vLN+yzH9YlbRmPVh4ewaPIIrJgZ6pOa4LN9fup8dqEE8rINPeiSBEWuUFeceHL5JptLDU7OgEEv5+iKk80lv7NxCLSrj2UZFAfcFgdCQshZufx0t4+54mSUj3zkozM4F4uTJyOm68CR1igGFvTLSPnpHFUzEdmWneSvW7kTdrnmmXebcPekShBCHGUY9Hwwbt+w8xgYArw4exx8blY7rr//BG/vPo57rq+CqmaOONOTcbZOfee7LCk/eU6GEb9G0TRU2J/uRO9SG8zLYBjtQhlNWmTHRcV00nUH/eZlGUQFSU9CPheLdxZ9Gcs379MxOk4IurPVHTk5BHaFhTLWE5cUBNwcoCZxPUnnQSedtFM7uoOiyraTWT7ykY+zjygv4dHf/j1rDwzGBBl/fWgSOJbVr4uSLGcUVffszBDGDx+oc563HTiVUYfB2lGlKC30gCR1s7WjSvvMdet80rPa5bxnZ4YQE2QQmHFs9V+7FDdfPhiEANsfvgGCaN23pYOHnAJjuGLIABxpjWFggQdBT99aXqDH2udidPSsqmos7Ejy5pidY7Exfx9rj8OdJOGEE6LtXKgvRZ62kQyKV7vXYKG9oi6E4oAbLGt/ottbU4bgZhnctWaHyTJ22aZP0NLB44lbRuPNjz7DzKsu1u2s01lcMgzRkU+pbWv4tA2XXVikl21nu91V2d3t14uzxyImyI7j092x6Kruczkm59LHLqLXP8l52kY+uhk5e646XbcG+N3gMoCTy5ffe3GO19ycpW2k9ufZmSGMvXgA1v7lCOZcPQS8pODetY2YUl2KqdVllmPmd7OYt7rBlPO9LgaP/t/f0NLB6/+7GAYFXlefmizSsXntz5/i5ssvxJsffYabL78QS9bvSnvs7fJ3V3OhHIluNSQ/eU5GhJfw0gcHLXc5v/OlYY53Ac4GMWfE1NRPG4X6DXtNuJqzRb+NH1aMlbPGYP6aHXhx9jiAwPYb3LnikOxg6PNWO5eTDdze2bQ9w3dBev1TnJ8856ObkbPnajghYsv+k5Y7t9dUlWTkzm22UXh9vfxsxjnmlZydPAPmHBLlJdyxugH100bBwzHY0NiM2uoylBd5HY9Za0QwIe1OhnlT3n9h9lgE3FwuTRK7FfRY03kL/d3VsXc6R7qaC+VA5FF1ZxN+N4tn3m3C8nf2669xDME911el3cdO02OHmDNiaqhWyqj9scPJ0Q+zk/au0OfCXw+3wedmEBcV2yWU1DbSJSe/m0U4IcLHae+1m3ga26OoqqN+SVFUQAXWfO8qhBMigh4OB05G0+L2IglJl7OkTnaNFzGnOsMJ0WJ5mjp+sqzo40d1106rCPnIRz4yGwEPh017WzCspAAFXhdaOnhs2tuC2uqyjJWfTU1yXy8/m9e/81XPyhCNgkKPDc3bdG5w8PGbHI/Z5Y9shqSomFZTjiVTRqKfzw2/h8UHD0zEk7//RD+uEV6Cj2MQl5Rue0HYRVc3jDJ1Q4keazpvob9Tx4DOBWidTudIV3OhvhL5mUQyzgUb5LSPnRV304mI6e+zwbRFEvbIp464iAWTKtPiYIxtrP/apbjpsk700h2rG9AWF7rlZOiEqUmIslb/6u0Y+bCGczrWnsCmPccdcXv7WyKOrkvGfu9vidjWGY5LumuZU3vtXA5bowJkOUOP4ucjH/lIGwnBASWXIUxXzAGFF8sQCi/bqL1slp/t69/ZYstyPRRFRTghoi2Zyzriop6rjZhV+roxKIbuiiEDMK2mHD/8yiVQAd1h8IFf7sIDU76Ak2EeIx7aqCPuPo+jcFcYuExi4uixpvMW+jt1DPS5QLJOJ2Sf3VwokpD6HMIuP3lOxrlgg+z2sbPvXDp9NFa+36QjazbtOX5WmLYdn7bZIp+2HTiFuROG4t40CDljG2++fLAVvfRaI07HxC5xMk6YGkWBBUezZP0u1FaX2eL2nrhlNJ57r0nHSs2/rtJUp7Hfz73XZMEGPl0XwqoPD3XZ3pgo22KmzhdMTj7ykeuhqKo9Si5DUkGGEPtrNsnMsrjbAbXnztCyu8uhfFcGys/29e9ssWW5HjFRxumYqJ+vb37UjBV1IWzacxwBN6ufZ281Ntsesx2ftmHp9NFYNHkEooJsOe/ve2MnBEmBpKioTWqmzTmse3nY2N50GLhMYuLosd6057g+f7HD+abOBeyQfca50NPJ8X3iltF4ZeuhPpeb+5RsgxDCAtgOoFlV1a8SQoYCWAugGEADgNtVVRXOpexzwQbZ7fOz3/0dy6bX6K8da4+DAFg+I6TTNr7zpWFnhWmb+8p2vDJ3HH5++1gEvZ20jWuqShyX/ugyiLGNVOaR+t6unAwBZ0wN0rgppeL29rdoyB5KB3FyXaLl0ffVTxuFqtIg9rdEUBxw45l3m7psb7aXRPORj3ykD7/TtSlTqDc3i2W/zh7qzeVi8fGhVv26G0lI2HGkDdeOGJSR8t0uFhu3H8XKWWN0Tfhbjc24ffyQz112tq9/Z4sty/Xwu1kTjrX+Nx8DAGZfPQQFXg68qODF2ePg97A4HeV1/GJHXMSbHzWj/jcf4+ZQOZbPCEFV7XNieZEPABxlD93Jw8b2psv7mZTV0GP9nS8Ng8/F4NvXDIXfzepj4DQXSEX20bnQk7dpLo0Dg27UVpeZMH59KfraTOJeAH8DUJj8/wkAT6mqupYQ8jyA7wJYeS4FxwQZc66+GGX9vCAEKC/yYtmtNYjyEliG2GpzjYi0aTXluHtiJZ68LYRwQsRz7zVhw85jmFZTjkWTRwBIItvQfUybEX8z95XtuiifPkxSwDKIJJf+7DB3Po5BTJSxfEYIHXER4YT9e09FeJPFrR0OrrvtpGXq0hReBpI6stSHDK4YMgD/OBPX647yElhCsO/RqehIaqdjggQk7ySV9fOiPblsZulvsh56fKJO45LyvnzkIx/ZiSgv4eP6G8Erqq679SQ/m5l4IC7KS7aIykyi5OKCrN8pV1QVcSGzKLzf7WnBjzd8rL82flgxvjnmws/dfqfrX6bGBrB/TqevRkyQcSrMY91dX8SI0kKoqsYRpxIaSVFx4GQYw0sKcM//NpoemptWU27KYa0RwXbsI7yErUsmIu6QM+3knglRhqLC8gWlK7xtd/C33Y1U7TR96LHAqy3LBw1abjtkH6ChbilWl86JiGGF6Fzb1pvRZ2gbhJALAawC8FMAiwB8DcBJABeoqioRQsYDqFdVtTZdOWeLVUqHg0tFuBjRLUunj8b/+1sLrr+kFPevS490sYvuooCc3tff57L0xw43t3LWGAiygntfOzccnF09nQiaCh1VV1roweLakaaxePZbIfCiisXrdtqibJ6aEYLXxWC+AXW3ctYYJEQF33/dHn9Dx0hV1bSYnC6OQ6/PqvO0jXx0M3L2XO3rqLe+XP65oFd7IHKWtqEoKgRJRkJSEOElU56i+azuygo0t8cwuMiPtX85YottWzCpErOvHmIpY9n0GqxvOIpbx12EzR//w2ZeYMW6Pp/MzQsMuZnmLQBp5weZwreeTTldoemc5kRLp49GgYfLJYTf+YWqI4T8EsDjAAoALAYwF8CfVFWtTG6/CMBGVVWr05WTDquUDgdnxKukIuaiguSIr7F7vbtYlu4+LWv3Pqc2vTx3HMTknaCOuAheVLDw9cZzxs68MHssXt5ySEf8UdpGXJTBMgTffaVzH/qNs6LYjxgvQ4Vq20bjWNuh7n4xZxxkVevDkdaYySjG2Hbj0+bp3mcTvf4Jzk+e89HNyNlzNdsotggv4URHHCUFXv3O9slwAoMKfRm5g9UTqLpsovxykDaUs5NnQDserREBD/5qt21Oqt+wFytnjcHqDw+jtroMw0sCiAky7nzVfI4suqEK37lmKAACv4dF8+k4lm76RDdeq582Cs+919SZCx1oG13hYXuCtnE2SEIj7reqNGibc53mRDmGZzx/UHWEkK8COKGqagMh5Lpz2P8OAHcAQEVFhe17jBoxKsGoHBQEL8r42a2jMbi/D5sWXouV7zeZUGkJUQYBwZrvXaXzHTfsPGZr2wk4645MJ7rBlRAAoGoyg3ROhvR99IR2qtvtYuEGMOKhjdpS1GP26B2/m9Wwd25Wezo+iaKz66Md4m/fT6cCAKZUl9pq+vzu9Hpp+redDsxLLy4Ablj+Bx0PRI9ZXJAQ4yV4XJ2JIuBh8ZObq/F0XUhvR67hcbpznuYjH7kQZ3tNpZFJ3a3fzeKCQi9kw/2fCwq98Gbocx3wcLjzy0MtmudMoupOhM00ohNhPmPlE0L0pXHj3/9McTbX1ICHg9+tnbOpuLkYL+HF2WPhc7OorS7Tc6Axf5pzkAyfm9HzLI2/Hm5DVWkQj33jMvjcDKK8ZNIN0/ztT8pE7XIuzVtdyWYyIavxu1mUFnpMss6V7zfB52L0+QFtuxH3e+Cxm/TcbOz7+fQsUl9p8QQA0wghNwHwQtM8rwBQRAjhVFWVAFwIoNluZ1VVXwDwAqB9+7R7D9WIlRR4sPjGkViyfpcuNXjgl+Ylhrgg447VDbZShCduGQ0AOBnmnXW3Kdoeu6URs8Tg7JZ00ml+o7wEQoi+jWqTLfqshIQ7Xz33PkZ5CS6GYGp1mUl2saIuBFGU0cHLkGTFUS9N/7bTgdG2/fz2sZZjZpSEnI5pkhDahwUp0hRBlOF1585HoDvnaT7ykQtxNtfUbOluJVFGhLe6nnKEwJ2Bz7Uoyri0rB/ufLXBcv3yZKB8QZRtr4+ZuC5lwXW1T8bZXFOpXnnBpErMvLICvKxg3urt+vg9eVsN4oKsYVhvHIkxFUU6os4uB62oC2HBpErTjaUrhgxAOCFh1dZDji59gFWSYcy5PakNToiyrdyyNSqYpJ7PzLwcAQ/b5byiJ7T4PRV9AlWnquqDqqpeqKrqEAB1AN5VVfVfALwH4Nbk2+YAeOtc66BYokWTR2DJeg0zM/+6SlvUUkdcdNy+ZP0uLJo8Akunj4aLId3C+dhhZcwYNyvG5nRMxII0iDq/i7VF6vhdrAkztPL9JgtOZsXMEF7ZeqjbfXSqR1RUW1ySoKhY8NpHUFQ1LcrmqRkhC/aPYoG2HWzFK1sPWY4ZrSeSkLF43U7HPty7thFiH+NK5iMffSk8DtcGT4Ymb7zD9YXP0OdaSHP9ykQ4XR8zcV3KJKrsnyXcDEGR34U5E4Y64uaigoza6jIsWb8LN18+GKs+PIQnbhltm4PuXduIOROGWs7/VVsP6WXYHR+7Y0dzbk/jABUFlnGIJGRbPK6ioMt5RdOJsON8oa9F7tx2O7dYAmAtIeRRAB8B+MW5FkSxRNeOGKQvKzghZQYVetNuryj2Y9HrjVg+I4Riju0S59MdJ55U+YIRq2Pchy7psCyD4oBbx8mkat6MmKGEKOsYnpggw+didBxct/rIMrb1BBjiuETz18NtuKCfD/e90WiL9dvfEsFjb/8N37y83Lxs+mkb5r6i6daeebcJ/zqxEgMLrPUYx8epD31xqSgf+egrwblYFAGma4OHIeAylCj7ugNgNss/Xx0AsxkuFwuWYcCwmtwhHU7ur4c1h99n3m1C08konq4L2b4/6OE6cysvw5vMrXdPqkp7fJxyLlT06MqB32M9jxznHh5NupFuXnH14+/i4a9cYpJyBj1cb2vxzyl6fPZACHlCVdUlXb3mFKqqvg/g/eTfBwFcmYl2RXkJu46eQeii/vjk0aloOhHBsfZ4WqSM09LE/pYIWjo6l1ecbLe9HIN48oGOdxZ92SSuv2LIAMQFGY0/moxtB06ZcHLhhIi40AWKzc2ClxUQ2GvejHoov2GJkD5sSHFxTvWEExKWTPkCACAuKRq+hhDT0kvqEg21BgeAxh9NRpSXdObj919v1B+oePybl5nwU0MGBhH0cmiLCvjVR8dM7fjsdBy8ZJV/UFeorpaQ+tpSUT7y0Vciyjs/SJ0pVN2WJdch4HHpk/MoL2YUhZfN60Y2259JVNk/S1DZRpHfhfaY5t5LH4SPCxqyTlVVxEUZ+346FVFewt8fmYKIIOlOvqnjHRckyCqSrpcEn52Om1CudscHKhxze9BrPnaZsuBODVquXVuMudWo86Y+FkxyLOk5rSoqgh5OR9nV/+ZjnaNNrwcBQs6p3dnqf3eiN6b7k21em9rjrUgJH8ei7soKzF+zQ7eS9XIMnrytxrTEYJQS2C1NdOUgSLVoH+w7gTaDfeqDv9qNB6aMxM2hcl2+8PCbuzF/zQ6MHz4QhEC3uZ2/Zgfigmxp24q6EBgCzFu1HYteb9StRrtrz0nbdsfqBoxIU8+y6TUQZRmL3tiZtmwf1ykd+Y9pndbgi15vRHtcxJ2vNnTa9t44EotuqDKN782hcjwwZSQe/NVu2zFaMVN7r53jUdDLYtn0GuclpLoQfFz+Lkw+8pGtMH7+s/G583EsGMKYLKgZwmS0/L7a/vPNAbAnwsexKPK7QAgwqMCDuisrUL9hL+57Q8tXH+w/acrZd6xuQFtMwLYDp/Dwm7steZI+H7Vq6yG0x0Ws33EUQa/mVujk0ufjGMiKYluWrCimHJtJC25jGMt9+M3dltxZ5HfhydtqsOiGKiy+caQ+L7ljdQP+cYZHTJRsbeHtzsknbhmNl7ccOqd2Z6v/3Y0eQ9URQuYD+FcAwwAcMGwqALBVVdVZPdGOs8Uq/WLOOA1S7umkYLjZzjvGiSRE308lC24WcVFx/AZE0S8UgWdBwMweh1MR3nQX+v3F19nic5ZNHw1RVlFR7Mf+Fs3cZPbVQxB6ZDM2LbzWYkrSFSbPCUuzbPpoBJIcxqYTEQQ9LBYndVDpyo7wEj7YdwLjhw8EyxB9fJ3atnLWGPzorb0YU1GEmy8fDI5h7FE9s8ehuT2OTXuOY8aVFWiPiRheEkCEl1Doc+mIHAAmagrF23UDadXrT9TkUXX56Gbk7LkaTojwMMRiksIrasZQb30ZJZft9vfmXTmHyHlUXdOJMEaUFkJRVUu+csrZK2eNQeiRzdi6ZCJEWcVFA/w6IeNkmNcxdxRR99BXLkHAzcHnZhBJyCjwcogKEgJuDjFRxrxV2/XcnlqWMceeDUbubCK1XCNiNspLeHnLITSdjOKRr4+yHQ87vCw9pyna1+/mTBSRc2l3tvqPHETV/S+AjdBYzf9ueD2sqmqb/S49F076M4+LQVxQtBcI4OVYOH3h6I6DoN/NYkp1qaNVtt/DokhxYUxFEQBt8ldRbK8xuqCfDyMf3ohPHp2K2qf/CI4huOf6KmxaeC2qSu11vlRTlcoAZQmB383qH3BaN8XueF0MRj5sj7ejSzc+F6Mj/GK8DIYAN156gV7Pz24dDYYAZUU+27YVel149ObqTgtyN6O3x2jpTfE591xfhSgvYePu47rM4+DjZkTOhp3HdHTe8fY4/G4Ox9oTWPl+U8ZsfPORj3xYI+DhINk8oJZJzfArc8dBMEzO3QyBK4Oa6utHDtIfQGQZgutHDuozmu1sOwDm4OT8c4XfzcLvdsHDarrn0kIPPnhgIgb396G00AOOYWzRcYU+F/7+SK3JP2HbgVPYsPMYbg6VY3CRD2u+dxXiSbzqhP98F588OhXDf/A2gE60K5PMwcbcbkS9cQzpRMgm0XDnhMI1HCu712m5drg+lmhzjBgv2+qh7Z7PKi30gIBAUbW6fC4WTSciqBwUxN0TKwEAb+8+ftZ6/N7W9ffY5FlV1TMAzgCYSQhhAZQm6w8SQoKqqh7pqbbYhZ2+bcGkSrRGzI45z8wMwcVqrnd2GLeucEAUT9RyJuGol67fsBcr6kL4Wk057vnfj1A/bZQj0u2KIQNwrD2uvxZJSKjfsBc/u3W0g25Kgs/F2jsB/TqJxqsLQZDNzn9G7I5RrzWtphyLbxyJNz/6DL4U9I4RF2esp/m0vZY8wksmLBSVwCy+cSQAbSJM35eKdwKA+t987GhBfqQ1Bo4luO+NRt3tKCHKJr13PvKRj8yFJMpoT0gWlFwRkBGUnCTKOJPl8rPZ/r6M7TrfUHi0PwdPhtHf74IK4IEpX8B9b+zEsumjsbh2pAlbZ0THRXgJiqJi9YeH8cy7Tfp5MqTYj8rSAst+lSUBHccK2NtqO2miw3EJqz48hJlXXQyfi7XP8d1A4T4z83IM8LvQFhMtrwc8rCOuzzhPeD6Jik1nMz6tptwydivqQti05zi+khwrOiZnq8fvbV1/j2ueCSH3AGgBsBnAb5M//9fT7UgNlhCLtmfOhKEWlNCC1xrRHnNG1XWFA6J4IjtM2xO3jMZz7zXpmJtwQsK2g6147r0miz6KTiyXTtfu5qYi5hgCWwwcQwhiomzplxGNFxU6MW922B2jhvjuiZVYsn6XLXrHiIsz1sMQWPqzoq6z7UY8Dy337omVlj4a23bz5YP18uzGdfnmfaY+3r9uFxSlB0+wfOTjnyyyjZLr6+VnG+WXzTjfUHgxUcOvjR8+UMMRSgrue0PLXYpqxbVRdNyKuhC27j+J9piI2uoy03ky5uIBtvvNnTAUm/YcNyHcqBad6oLtNNFP3DIaqz7UMHcLXvsIDINzRuHSY2X3uqIAcx1wfcYcuiqJik19HiroZfXXFk0eYYuJNY4VHZOz1eP3tq6/N267LQQwUlXV1i7f2YPhdbNY9utPdGyapu1Nj6txQqClWzaxw7RVlQaxvyWCZb//xCRPoPVs2HkMYyqKdLxLJKFpq2ury7Bs0ydYPiOEF2aP1R1+AFgwcE0nIvp7afmp7aZoPCcUTYGX07FTCUHW/6b7pjoRXdjfXp5xQT8fPth3woSg87s6257q1FRa6EFVcvxgTgAAIABJREFUaRAvzh4LhhDcPanK5PJkbJvPzUJRXfjFnHHwullN/uFi8dg3qhEVZJQUeDqdIj35h2fykY9sRcDDYdXccRbNc1+RPWS7fM7FgiREE8ovIUgZG59sRm8vmWc6aH+onLLcIC0sd5AZVhT7oSgqNu1twY2jygB05q7hJQHERRn/M+8qPV8fOBnFyvebEPRymDthKO6ZVIX9JyKmu/UMQzDA78K3rxkKv5vVcqSHw/4T2vzg7d3Hdcyd18XCa0ThJp/JAtHoHvQZH6dj5eiAnMyLTtvpPIGiYimOjj7zxYsKXpw9Fv7k58TOobCqNIimn05FNEkQiQsSEpIMr6v7EiCGISbkbk9Lh3pj8nwUmnwjpyLKS2jp4E2ItPcXX3dOqLpUpIxx2eT5WWP1ZRlan90DdMZ6ptWUY9IXSk1SBXqX+mSY16UePzcsoxjLpzF+WDEiCQkq7FE4dCnJiKIxbjdKSvxuFnesbtAlJf84E7dIWJwcliIJEZeWW527np0ZwsY9LRanpqXTRyMhyIgJZjcxunRWWRKwOB6tqAthXcNR/G5PC56pC0FUVNz3hlk+kpdtZDaG/Ptvz+r9h//zK1lqST5yIfq67CHb5ScEGbysYsHqBsu1zt8Dy86fJ3p7yTzTEeNlLJhUqTsGGnO7U54/0qrl58W1I3EqwkOSFV3CmOoeqEsQa0cilpQnrqgL4eDJMAb39yHo0UQAiqJapBQ019MH62h7jChcRdEQegte+8giJ31n0Zdt298RF+3lkwkJbVFB/99pnkBRsSUFHpwK85bPuc+l4XJT5wVLp4/GyTAPAmDtX47oUhezq3L3JEDZ1vWnrbtHa9PiIID3CSEPEkIW0Z9eaIcp7GQbAXcn7oy+tnxGTVpU3dLpo7Vvf4YwL4/IuuaHLss4ufHQeqg0wm7ZyCj1eMWwjJLOOVCSZctyi9HZj6Jo0klKaDuopIQhxHZ5JtVhaen00SAMsV0OvaaqxNap6f51uyCr1iVUOgZzJgy1OB7du7YRXw8N1mUodAnOWGZetpGPfGQv+rrsIdvly6pquywu9xAB6/NEby+ZZzoYBpgzYShe2XpIn+gaUad26LiAm9XlgD4XC4YQRwkjff3+dbsQ5WVTzjOOmZO7IJUtOqFwjfulykmXb95nK2V886Nmq3wyOUdYvnkfAm42rQPwipkhBL0sFJvcfO/aRsRE2dah8P51uyBIikW+YXZVzn0JUG98RTyS/HEnf3IiqGzjxdnj4HNrT4P+5Ld/AwCTtOLxt/9uklAcb4/jZ7eORnmRzyKNoGFcNinye7DmT4cx++ohKPBy+rJMQuyUQXTERbz5UTMA6PU4LRstXNuoSz3oMgqVavzjjNa2wf19+pIKdTda86fDetnhhARBknVnv6CH09E6TpKSQp9254W+ls5hyU464rSMlG6p1GkMVNVehkLbmM4RKR/5yEd2oidkD/1gdjB0Z1AW0tcdErMZvb1knunwulh4OOiOgXdPrERpocdWphjjZZyJC/jJb/+m05yCXg5Bb6eE0Unu8NfDbRhY4NFfC3g0czEaThKLqtKgLs38zpeGWcbauF9q/Rt2HgNDoMsrjPl8x5F2Pc8b3YUp5WPJlJH6nIg6AFNjs+KAG/e9sTNtPqd/p26jUhgqATGOEf071yVAPf4pVVX1P3q6zu5ElJdQO6oUiqqCACjr58VTM2rAi4p+IpUWejCmokh3yHHiL0d5CQQEfo9mUSkrqsm18Hd7WvDjDR+btL2yqsLFEESTJAlKshg/fCA4hrFdPmk5k8DdEyvx1AztZN605zgivGRCu40fVoxfzB2nOwxu/fdJiPASbv/iEHQkRCiKCkmW4U6C+Qf39yEuahPpSEKCIMq2kpKOuGgav464qPeR1k+lJ3bSESeHIpYQx6VSJymJh7MfH9pGJxlKX11izEc++kJEeQkf199o0TxnUlaRbQfDl7cc0l3mjrUnsGnPcXz7mqEZK9/oYkev4Zkan2yj5HpzyTzTERNkCKKMv/zgenhdLBSDDXZCkBHmkxxmXsK8lHPuiiED0BYV0BoRdAnjO4u+jIsG+HGsPQ6GaM8ghROaa2FMkHDw8ZvQERchiDK8BglTQpTxwQMTUdrPq0/S1zd8hpgg6+cElXiktj+dzKSlg4ekKIjyqimfb9h5zMSPjvGS3vZTYR4FXk5fCYkJso6xXTR5BAghqJ82Crwo6/s0nYhg24FTuG7kIADO0ifaxlTqiFESQvNzriIRe9Ik5WlVVRcSQn4DwFKpqqrTeqIdTqB0SVLQFjPj2/7rW5drcoEULe3GPcfxuz0teHH2WIsOd0VdCB4Xg7tetUfZPT9rDHhJwdq/HLHoolbUhXAynEBJgde0fUp1KaZWl5nrmRmCO4nMM+7f3B5DSYFX1w49P2sMBFnBgtcabduzfEYNfC7WEb23oi6EoIfDd1eZUTN+N4t5qxts99GWhD5D3VUVljYunT4aZ2KCpY90+1MzQvC6rP0a4Hdbjg+tZ/bVQyDIiuNxstM8r6gLoTjgBsvaKpd6/ZPZF01S8prnXomcPVftrqn0s8xxn18xmC/fOXIUJZezJimSpCAiSJAUBQlR0fPZgkmVmH31EER4Cb9q+Awzr6ywfX4m6OHQfDqG0n5eCJJ1O83HK+pCaPi0Df/2WqMlD2nHjMeC1xotZRd4OKdcBUDzbaD4Wac87nez8LlYWzxdcUATARjrXzCpEnVXVZjy6rLpNfC4CP7tfw3vubLCcg5TLbPddn1+cGVFl5pnrU09fh53q+CenDyPVVW1gRDyZbvtqqr+oSfacTYOg053ll+YPRbH2hMo9HJYt/2o5c7BtNBgXLfsfdsHAd9ffB02NDZj7oShuPNV612TlbPG4M2PmvHNMRfq2zctvBab9hw31VPkd2FhUmeUuv/8NTvw4uxx2imgQnfpc3L2o45ATttfmD0WigIU+DoB8JNGDoKgqCAgti6AP799LOKijB2ftukOXeGEBFlW4OZYfLD/BCZUltiOwfLbatCRkExj+u1rhuLlLYcw++ohKPS6EOElBDwswgkJbpbBJy0dGF5SoNE7eAkcQ+DhWP1OOADdJYm6MX7nS8PyDoMZjPzkuVciZ8/VnnAANN4ZNl4r+oIDYDbLz6L72ueJnJ08hxMiWiPaQ3LGnL9p4bXwcAwe/NVu3SnQyf3vhdljoajAXTY5rX7aKNQ+/UfT33QbPd5Ox+zxb16GgQWetMctwkt46YODSTmoC21RHh6O1Q3HXAyBm3M2RmEYYqm/q/lCuvcY+7johirMnTAUQQ+HiCAhkKzX52J1p2ZKCkmlbfTSeZxbDoOqqjYkf6edJBNC1quqekvPtKozjPozKiVwcvYLeDiU9fMi6OXwnWuGIsp3CtsPnoriogF+3eVv2fTRUFQNdxNOiCjwcqitLtP1UallF/pc2HGkHbeOvUh3MxpeEsAz7zaZqBUHHrsJd355qI57i/ISfBwLSVHw89ljdXQMSwhe/e6V+klKJ+f1v/lYr7Oi2I9pNeW2uLmV7zch4OGwcG0jAM118MZRZYgLMn745h5HvVPQq2m5Jl96ASK8BFUFIgkRigoUBdwYVlLgqPkbVOjF+P9823QsAp7kuHk4LHqjEfOvq0RVaRAtHTwqBwUw/fk/mdyYDjx2k8Wh6e3dxy1ujPnIRz6yEz2Bkku9Lmbycx3wcKZrbCQhYceRzLbf6Xr7eYO6sKaWnUkdaa4up59LaEg3s0Z3Wk05Bhd54XOzut75F3PGQVFV+NwcjrXHEfSwWD69RsfQxngNrWqMVC1vVWkQ02rKdcwqPd5OeueLBvhhkEU7ugLS55nsnAmpgyHgLLdJdRY0OgEb5ZWiJGN3/Y26FGtKdalpckv7SKUpbzU2I+jlMOzBTkfFTx6dCkLQKUUx0Mns2pQ6JmfjopityEWh0rDeqJRqc0oKPDoqzcnZL5LQUDN2yyNLp49GPKkTptsf+KUVWXNBv6GOmLvFN5odeZ62Qb7FBAmXlplxbyuTEg3jMst/fetyRHgrLgrQHPkocmfxjSPRFuVt+5MQZPzwK5dYXAeXTh/tqGmKJCS8svWQLsuwGwuK7Uvd90RHAgB098JUacvDX71EXzaiEpbU8XHSOZs0VSlIwXzkIx+Zi76OkhNF2XKNXVEXgijK8GQAtZcQZMfr7edF1SVEh7IzhOfMUVnIOUeUl/Q7z3Qe8OBNX8BLW6w5zCTDvH2MRXqzNHnDjD53lJp3aL4FNIdCer464f+OtsX0O89O4x7wsBbEnrGMrp7vkWUFUUHWnQUJA92t1zgnspWQ1oWgqtBvyNE+3rD8D/r2hNB5gzG1T+miu0jE3jgfewNV11X0CqfHlcQSGVFpds5+Roc7O4fB+9ftQjju7EBIkTWrth7CiplWDJKiqhbMzUIb5BsACx6mPSZakG3hJGc1FSNDHfmo+96S9bvg5ljb/iiqaus6eP+6XbaIP/oFwojssRuLVR8ewtM2yLwCrzOi7961jYgkZPNrrzVibsr4FPldlvE1YnbskIL5yEc+Mhd9HSUnOKD2hAyh9rKJqnNChGUKz3m+OQy6GIIivwtBr4ZnWzR5BBa9vrPLHKaq1jx8/zoNoWqXd4z5ljoUmt0FrTmrv9+lvyedK6CTM2F3EIIxUcYrWw9hztWas2AkIWNVEttnnBN9PTTYcT5hbPPyzftM2yVFdexTuuguErE3zsf8bbdkuF0sNm4/itvHD9GXCeg3R4py6YhrsgvqhOeEpBlU6E27vXJQEF95twl3T6rUlwTp8oaxfuM+Rne/jrhouyRqh2RzwrQV+lyonzZKR9ZwDEGBg5TE7+Fwkdt+m50z47JNn+DJ20IYGPQ44nMAJJeZKrFy1hgUeF0mlB0dF6dlrNTXgobxifKS/uGir1EcH8Xs2CEF85GPfGQuso16y7ZDX192MPR7HJa7M4TnPN8cBt0uFi6OQVtUwAC/G95k/4x5yy6HpcPIfvLoVMQFCQwhnXnHkG+pQyF9EFDD/3l0pJyuA+Y65QeO4+5hdYydz8V0YvW6KV+gEqi7J1Xpq7EU22fE0Dr1t9DnSvZXxsNv7tbnTnR70Mth30+n2vYpXXQXidgb52MuTp57Zc0nykuYVlNmWQrUUS6zx4GXFDC8PRImFbm29z9qQQjwzqIvY/nmfaYlnLggo+GHk0GSGiRFVhFOSJhSXYaYoXxjmQlB1gZGBRhCkLBZzrCTKjhi2ngJpYUePDUjhLsnVuqIJKdlUFlR8fdHpiAuadquuCCDl7TbGAtvGGHq4/hhxTgV4eHhGOx7dCo6EiIA1XYsjrbF9YcPptWUY9HkEVBVVdd42e8T09tn3McYoqyAS/N08rCBgTyqLh/5yGL0BEqun9dlMl3p53X1GVlIlJew7q4vdj7onJBw4GQ4I+Vn2wHwfHMYjPISAGD74TZcU1Wi5+GmExE8OzOE8cMHghDggwcmws0ReDhOf67I6RzRcLUaIzrCS6gaFMQjXx+F5bfVJJ8D0lwB/QDikqJNDpOaXVVRoUKF18XpHg2x5Bwg3bjTsS/warmvu8ciIWi4ubggI5wQwTBEx891xEVdFunkStgRFxF6ZDMafzQZLR28qWx9PAiBz80gJsgA0R5y7K4Nd1dIxN44H3Nx4XpJb1Tq41iIMvDylkOWZY+l00dj/Y6jEGUFW5tOWlz8Ft1QhcU3jkT9hr0Y+fBG3PlqA07HBCx6vREP/mo3HpgyEjeHyrUlh7oQOhIi7nq1ASMe0t7bFhOwp7kdoqxg/Y6jljLve6MRbTEB81Y3YESy/I6EhJWzxnQpVSjwcpalzSdvq0FckDF/zQ6MfHgj6jfsRd2VFTjSGrV1JZRkFdsOnEJbTMAdqxuw6PVGnI4JuPt/dmDEQxstffyvb10OQoD5a3ZgxMMbMX/NDjSfTmBDY7PpfUYXxZtD5XhgykhsaGxG8+kE7ljdYFv2ipkhFHi5tPvcsboBHbyESDJ5j3hoI+56tQG8pOC+Nxr1/nrTTK7zkY98fL7wcaytrMLHZeZukI9j0Z6QTJ/79oSU0fKz3f7BRX7cacgFg4v8GSnfyzK2bc/UNc/H2ZfvywDCrzfCx7FwMQRjLx6AO1Y3YP2Oo1gxM4SYIGLsxQO0XPbQRqzbfhSyohGsRjy0ES9vOWQdh5kh8JKMeau3Y9HrWu6+69UGPRcea09g9YeH0Xw6gS37T6I1KmDeKq28eau2ozXKI8ybz2v6XklRLTn6mZmhz+XsKMsapu/BX+3G+h1HUeDlQIhGHRmZbHPdlRVYdEMV3mpstj3uBNoX43TbX/rgoClPa30VoGRABtUbjpc9iap7Q1XV2wghu2HWNRMAqqqqo3uiHd3BKtE7vlWlQRxpjWH55n24e2KljmSp/9qluPnywSj0uRAXZCiqanuHxYineXH2ODS3x+F3s3jgl7scEXP100bhufea8NNvVOtlOuFgnv3W5fBwjL5k6eNYnEkI4FgWBUkCB0sI3Byj0zaOtMbgYgkWr7Nvw4/e2qsj3ej+3121XW9fuvZ01UeK+qHv27TnOGZcWYH2mIjBRT7MW71df49T2Zv2HMf3vjQMgqyAY5i0+xiROnbHJM0dsF5/4iWPqstHNyNnz9VwQoSHIRaTFF5Rcx71Rsvvq+3PNsaPotFSy0+D/wRyHFUnK6opxxX5XfC7WdMxsst9i26o0hFx4YQIXlJ0jGw6lFv9hr2mvGrcbpe76HtLCjz6ivTRthgGFXo+10OgxvPQiOZLbdPzszQpJS/KkNXOz4SLIXBx2h3lgIeDIMoQFBXBpMTUyzH49itpcnuGsHMZpG3kFqoOwL3J31/twTq7HXbYIEVRccPyP0BSVDw1I2TZXr9hL5bdWgOGJY7aZvq336Ohg9JphqZUl6KqNIgffvUSkx7OSTvd369BxEc8ZI+moRdJSep8SuSG5X/AJ49OdWzDmIoiFPk7L65ujklqkjvHp6rUvj1d9ZH2w+9hcUGhF//yxQr0D3jQHhN1jZ5TX/0eFs+914S7J1bCzTGQVbXLfey00cZj0hdscPORj74aAQ/neG3KVPnZ1iRLNg8c9QXNc7YxfhSNlq3yezpSraSHlwRACECIObc7P7tTheE/eBsHHrsJBYZyurLqdsqVdrmLvldSVF3GqGHfpiCSkGx10t2ZUKbONYih/cb6g14Ow3/wto6yIyD680QcCxAQLHq9EW82duqd6ef9r4fbMLwkYHo26rn3mvD27uMWXfK5ToJ72vGyx9ZYVFU9nvz9qaqqnwI4DSBs+OnVoNggKr2o37AXbVEBCyZVAgD+cSZu2f7Dr16KtriAI62artgYqXiacFyz3d7fErF975HWGKZWlyGS/OZqLJNqq1P3OdYe1zXNqduohou6WN2xukGv26m8KC/hpsvK9CWqO1Y3oC0qYNuBUwgnJDww5Quo37DXsQ9d9ZHWu78lgrvWNEBWgFe3HUb9hr26ZbdT2yIJCYtvHImDJ8Noi3avP0ZttHHMUscoH/nIR+aD6kGNkcnPXbbLl0TZVhZiN6E+l8hm+7M9NlRjmlp+TOibtI0oL+l63mk15Qgn0XX0NRpOuYbm+qYTEVNOTvd+qhXubu6ye++CSZWa7CMpI5m3ejvaooJ2Jz3pOmiWhFhlEsZzpT3GI+Jw7jSdiGBaTTl++JVLoKJTunLXqw1o6eDx0paDWFw7EtNqyi3tpu00zp8W3zgyaVfeec5Q5FxXbc6F6HGBEiHkTkLIPwDsAtCQ/On19WnFBht0rwERp6hW9E84IeHe1xqxfPM+W500xdM8XRfCqg8POeLvKL7m3rWNAAjuX7fLVCbVVqeW7+YYW52zEX8Tl2QdLUPrtsPZLJ0+Giwhthia8cMHoj0m4r43djr2oTt9pPU+916TXvbXQ4Ox7WAr4qKMpdOd28YwBEvW78L44QO71Z9l02sQcLPWcgj0MXL1QR5pPvLRVyLbKDmXQ/mZ+lzzDqg6PkOJPJvjk229dm9oTLMZPo4FxxCsmKnhas/ERNy7thFvfmTW8G7ac9x2XDftOa5vL/K79Hxtl7uNOWvbgVOW8uxyl9N7504YasHT3r9uF07HxG7j28yfIxavbLU+97ViptbHuydWIirIlrnQ4nUa1i8V06dZcTdjzoShupTFiO2dO2Go6ZzpSwjE3li3XgygWlXVU71Qt2P4HZbQgh4O9dNGYXB/n2U7xcDRZUm6JBEXtCdLl88IYX9LBMUBt463S8Xf7W8x42soni21TF6U8bNbR6O8yGdCrb267TD+5aqLLZg2ir8xLsnQuh/7xmXwuhhbRJyTnKPA67KUY+xDuj5SxF9tdZneV2PZADAw6MF9bzTi0ZvTt824zEXLuXtiJQb392LlrDEo9LmwvyWCJ37395RjoiF0ls8IYeWsMToWMB/5yEd2ItuoOooXpZ97I+4zE5FtWQjnYhFUVdP4sAQZGR+OYzDA7zaV7eNYcBl6oK+7CLG+EhzHwAvA52YxMEigqtqx3nawFbOuulg/x8IJCVBVHScXjmt207OvHoJ7rq9C8+k4vBwDN+vW35MQZDx/+1gUeDh0JEQEPVxSI80hLhZggN9tyqV2ucvnZtA/UAIfx5rHvAtXwu7g24yfowIfpyPqjBKL4oAbs68egkKfSx+b1HKpFIVi+oxoPicEL3UiptGXEIi9MXk+ACDW5bt6OGJJd53UByDioowLktxmik0DtAlbKopuw85jurA/9Mjv0fijyajfsNfiVEjxd49/8zLd/50i1wANh6OoKi7op02Un3t3P6aFBlseIAgnJNx46QX6BUtDvJFOBJ6iIipY0XuLJo+wfSDACbvTERfRHhNt+7By1hi9j3bjB5Sh9uk/6mNhh8zbtPBaEKIh787EBcxbbX3YMMpLWDCpUpd3pLbjhdlj0dKhuTUZ66HHpH7aKLR08IglrdQHFXj6LFYpH/noC0Eny3avZwr1NnPcRfqdYJYhmDnuoj6Fqtuy/yTGDx8IAJAVFVsOnMI1VSUZKZ9hOnMBIaTPTmx7KgRZgSypiAkyPByjH/uWcAIMISj0ucASgjMJEesbPsOcCUNx1xrrw4SpD/ZVlQZxojWGH765x4RzpQ/Q0d/P3z7WNne9OGccWIbpxM9xnRi6iM05umBSJcIJEYU+ly3qNTXvCaKM28ZdBElRkRBkfPDARJT28yLGy/jHGe0h/fJrhqI9JoIXFcRFeyxc04kIFkyqRJSXknbnLMZUFNnOlZza0pcQiD1G29ArJORyAC8D+DMAHQioquqCnqjf6Ylbqg022U7ODMHNMpi/Zof+2rPfCoEXrTbVyzZ9gpYOXpNMeFjMW9WgW1mu/csR3eLTrmwnm29jmR4Xg7te7WzHsuk18LiIyaZaWyL5DDOvuhgD/C60xURsP9yKsRcPMPXrv751OeTkkqTRYtPvZhATFMvrDZ+2YfzwgUiICr7/utmGtOlEGJeW9UPDp22WelbUhbBxz3H8bk8LXpw9FjFBNm1fOWsM4qKMRa93juWTt9XAxRAsSCmHQIUK0mU96cblm2MvNI3pAL/b6U5Mr2eZPG0jH92MnD1Xba+p6T93ZxX58p0j23bF51h+ztI2FEVFOCGCECAhKVj7Zy1nv/nRZ5h+xUWmHLV0+mgEPRzcLIP2uCZn/OvhNiyYVIm6Kyv0fBnhJcecTnPSLWMvwvqGo/jm2AsR9HCQFMWUu56ZGUJxwOM4ptpx4LHgtUZTG1Ltwmm9qcdIlrXJcEyUsfbPR3DbFRWWHB/0cGg8eho//8MhrJw1BrKi8amNfVs2vQa7Pjttys1dtWVFXQjFAbe+St7Zn163fe9WRb0xef4LgC0AdgPQMRCqqq5Ks48XwB8BeKDdLf+lqqo/JoQMBbAWQDE07fTtqqoK6ervDqqOhh0y5v3F19netTWi1L4x5kLIioqKYj/OxEVwDIHPxSKSvGPRdCKCIr8LO5IfMopcS4e6+9mto/Uy97dEEPSwtrg5+i32hdljccfqBtRPG4VNe47rd4SPtcfh5hgUB9w6vq4jLmJb8o6HIMlwcaz2rTahSUAOnIpi057juGXshYjwMioHBRETNIydogIvbTmI2VcPsUXuvDh7HCRFgQrgTwdOYfzwgdryV1wCIcCdr1rH/MXZYyElcVD0DraxfCMqsCMu4s2PmlH/m4/1/Z+/fSw64iLKi3wIJzTJyNG2uMXIJY+qy2zkJ8+9Ejl7rvYESi7b5WcT95bN9kd4CfNWWXNKprBg51h+zk6eI7yEU2HtXh7N79NqyvHI10c5ouQAbQVTUaEbpvg4FnFJMzOZZ3NsX5w9DipUXXbhc7E4cDKK595rwskwj+dvHwuWEPg9LFrOJNDP7+oSQ6co2t1y2ga7c+rF2eMAAou0xojoS4d85SVFn4ssm65Rhfv53HqdfjeLcEIyjVVXSFsntGEGkXPnGjmHqqPhUlV10VnuwwOYpKpqhBDiArCFELIRwCIAT6mqupYQ8jyA7wJYeS6NctK3XdjfZ8LTXWijfaaanNJCD+65vgpRXsKvdnyG28cPwYbGZtwy5iLdGZAQoLTQg6Cbw7+9pnm+H3jsJtsyq0qDaPzRZBR4NZ70+h1HMeuLFwMAyors2zG8JIDnZ2k6t+dvHwsXQ3D3pCo0nYjg+683AtAkJyUFHqgqdGe+E2EeAQ+nST+S5RECEAYoK/Lie18aBjfHoFCUdfc/N8uAYQn6+V2OyB2/h8X+ljiGlwT0/tI48NhNFvzfyveb4Pdw2N8SwY/e2qtrwe+5vkovv/43H6P+Nx/jwGM3Ydyj75jK/OvhNgTcrMmlEACefkdjdT81I6TXk0fV5SMf2YuAh8MTt1Sjf8Cj625PR/k+gXqj5Y++qB/K+nlBCFDWz4vRF/XLaPlTqkstmu2M2HNnWTval7Sp3Qm/m9XxcMZ+0bxmdPul8wCGIRBsmxnbAAAgAElEQVREzecB0FBtkqLdD3R6hsrnZjH8B28nEXNT8f3XG015KeBikZAUqCrQkZAwqNCjTyZ9Lga8qEBRoTv1UQtuhqH9sK/X72FN2mJaphHR1xXydVpNOX741Uvgc2nuihFegmrIvalzAFpe6th5XQxqn/6jI9owk8i5bE7Ee8MOaCMh5A5CSBkhZAD9SbeDqkUk+a8r+aMCmATgl8nXVwG4+VwbZYf2WTCpEm0peBUjvo7GFUMGIMJLJsTb1OoyiKKMqdVl+GD/CbTFBN1Jav6aHWiLCXh2ZggAcKw9nhb9NvJhDUEztboMcUFG/Ya9aD5t3efZmSG0RQXctabTVa8tJuiuej/8yiVYksTNUUer5tOa29HU6jJIooyEqFicjV7ZcgiiouiIOB1jFxMgJfvohOvb3xJxHLdTEd6C/1tcOxLH2+M6ymZaTbkjpscO07dgUiXaYoJ+LOav2YHWqICHv3qJpZ5EH8Uq5SMffSEkUYbXxZmuGV6XPTv5XCLbODZRlHFpWT+TA+ClZf0gZqj9QvLaabxWTa0ug5CB8qm9tDG0Z0wy0/Zsl9/TEeMlnIp0Ytqm1ZRj8Y0j0R7TMGtGB2GazxKijA5e0px/k5i4joSEl7cccsS1RnhJz2mnIryp3E17jiedhLfr9bQmsXMvfXAQbREBbTEBL21JcepL4unigtwluhbolEa89MFBRBKdiL50yNdj7XH8+GuXgpcUHVF35+oGNLcn8PKWQ2g+nUB7VLBg/ezGrjUq6GOQTbRhtrF3vTF5ngng3wFshYaooz9pgxDCEkIaAZwAsBnag4ftqqrSs+IzAIPPtVEsIRakzJwJQ21RRXOT+DojxuWVrYcs7xOSumIjXs24/ZqqEowfVgyGwFK3Ef1m3If+bbfPhKoSSz33r9uF+ddVYtvBVkQFGYvX7bTgYmqry3QEU+r+dLuqwhHbdO9ae1xfKpYuddx8LtaCvLl/3S4oKvS6F00egaXTR+OtxmZLfwNuFk/eVtMluufe1xoRScg29eQeOzIf+ThfItuoN7trNkVuZiIEh/YLGWq/6FC+mIHyGcaaHzTkZwYa3gPl93QwRJNWrtp6CE/N0HB1S9bvgodjMGfCUCxZb8XYirJqzTVrG1FbXeaIa1219RAWTR6B5TNq4HOxpnJpHk7NXadjImqry3REXG11maU996/bhY64aMLkGecndji42uoybG06qSP6Nu05jmXTayzHNOhlwRAgnJAs+ZrOD5as3wWWZUx1b9pzHHNtxm7h2kYsmjwi62jDbGPvemPd+lIA/wrgGmh3jz8A8HxXO6mqKgMIEUKKAPwawBe6WyEh5A4AdwBARUWF7Xu8bhbLfv2JCc8SdMLXeTkzGi7ptpT6voCHw/83aww4hsGa712lu+ps2HlM307LWfR6oyP6DYC+9FHocyWlHByOtSewbPpolBZ6EeElHatH66DtGF4SwKaF16Ki2I9l00dDUbUlSKrBjgsySgs9jsuglYOCFuwNbU/AUOey339iwuv84Ne7Te0IejnT+DrVV17k0/+uKPYjIci4ffwQJAQZP589FoHkEgwd//+eMw5eV+cyVncdm/w5Jtvoznnak3G2GuZ8/PNEd87VbMsqvG4WTYfD+Pntmm1wJCFhx5E2XDtiUEbK7wlZiJ1sLRPle10sPCwx5amEIMGbocmK18Vi2SZzvqRI0VyK7l5TvUm5ycFTUciKgopivy6zcEKzFXg5/M+8qxDjZfCShJigoLzIh7ggY8mUkdj8cYue02O8lg/f3n0c91xfhYVrG7H8thrT+A0vCdjWQ3Ogm2V0iU+qHII+2xMXZAwMdGLyqH02iKZvDng4QAWemRlCwM2hclAQp8I8+vk4fPuaofC7Wf2cifEy4qIEXlRQVuTrElFX4OXw47f2dGsOVVHs16SsWdQyZ1ta1BvfE1cBuATAMwCehTaZdnxYMDVUVW0H8B6A8QCKCCH0SnMhgGaHfV5QVXWcqqrjSkpKbMuN8hJaOnjUPv1HDP/B26h9+o9pl0Auq/89hj34Ni6r/z2ijktYEqK8ZFqGMUoRIkn3qv0tEb1uKnM4cDKql0mXkKjcYv6aHWg+ncCvd3wGN8ugpYPXl/6MdQAwOfsser0RKoBf7/gMx9oTJknI4tqRiDu4RjWdiJhkE6ntoXUCQO3Tf8Ss//4zTkV4feJMy+mIi6bxPdGRSOvWRMf6u8lll++u2g5VVdEaMctHooKE9phoch1MLdPOsSnX3LC6c57mIx+5EN05V2MOsopYhmQVgoOsIhOyByD7shA7V9tMyckkUYYKYrpOqiAZk8zEeNmSL40o0FyJ7l5TtS8X2vFYvG6XLouMJCTHecCR1hhGPLQRL205CFkBHvjlLj2fqgC+clkZNu05jiOtMTS3x7Fh5zFNjpmQMKaiyOK41+ogCT3SGkNbTEBEkLD6w8PY32KVQ9A5wUtbDqEjIeGlLQf14x4RJJwI8yaZBy8piIkS7nujEQtfb8SJsICHfr0Hs/77L5AVFftbIpi3ejuu+On/w4Qn3sP+lojjOBjdElPPiSMO+2g67ew+BJhtF8zemDxXq6r6PVVV30v+zANQnW4HQkhJ8o4zCCE+AJMB/A3aJPrW5NvmAHjrXBtltwRoJwugy4LG19ysvVNUlLc68VApwoq6ELY2nbQ48lFHIqNr3t0TKy1LH3S5xEmKcffESl16Qp195l9XmXbZJy7Kln5QNyRCoG9zag+tc8XMEIr8Lst40L/p70KfdYnJ6My4dPpoEEJM9djKR15rRDghObob2rWnL7th5SMffSEYB1kFkyFZRTZlD0D2HRLtXG0zJSfLtmTmfJNt+F0sZMPxYJL57sDJMIr8Ltt5wPLN+xzlFvev24WoIGPOhKEIelk9p62oC2HV1kO4+fLBFse9hTbSRuo+fP+6XWhPyjeee68Jc662yiGMEsza6jL99UhCw8Gmti+SkHVJp3Fesu3AKYszYqpzYnfdEvv7XXgmxQG5p3Jvtl0we2Pdegch5Iuqqv4JAAghV6FrzXMZgFWEEBbahP8NVVX/jxDyMYC1hJBHAXwE4Bfn2qhU2UY46QQkSIqts59xOczO6erNj5odXXUqiv1QZBX/9ppGv0h15DveHsd3rhkKr4s1LdOkllM5KKj/nbqtqjSouRp5O5dN6PKK01O1/f1uvLrtsN63SEKTpNRWl+HHb+3Fsuk1+janOlfOGoM3P9IWAGjbo7wEn4uFJCv6/h1xET4Xi4eSS39VpUE0n46DAHjytpDjMqDTWFBZRupY0qXcL1WV6EtZfd0N63yJPNru/A47KVwml/Z7wgEwEU6YrvWnozy4Ak9GynciMmRCTpZ1yUwfkW10N1iWQYAh+phd0M8HVVXhd3NJx0AGL84eB5+b1d1qaa5JR6kgBEgImttw8+k4BiTlmEZ6lHGfoIfT6zE69HEMMeW4pxzcgI05ngZ1QrZrn/H/imI/RFHGl6pKUFtdhoQom3KmzzAORkQdlXsMCAwCx8CSZwH0ihNltl0we2zyTAjZDU3j7ALwISHkSPL/iwH8Pd2+qqruAnC5zesHAVyZifYZZRtUS1QwyAVZVU24lGEDA6ZlQZYQRHkJ/3LVxYjwEmK8rLMOxw8faOuWE0lIOH4mYdnmSYLx+/vdkFVVv0OTcHDdaToRMTkhGbfFeBmRhKj/v+1gq768Qn+n7hMXZIwfPhAxQTaxIqn7IT3pqNtfKv80yktgCMHsqzV9shEhRwB43Ry80Jia2w6cwoTKEiyfEUIkIUEQZTzwSyu3mjoQ0nroUnBq242yDKP7YeiRzRg/rBhjLx6AgFuzAs01p6J85ON8DOM1lQZ1C+0rDoB7j3WYHAD3HutA/4AnY+U/OzOks+8pbz8T7c/22MQEGbWjSlFa6NHxq7WjSnPSCa67YRyzphMRFHo58JKCDY3NqK0uQ1VpEEdaYyjwslh4wwj9Js8/zsRtxzqcEOFOGoCcjvL49Y7PcMvYC/HOoi/rtJLUffYnJYuUjzytphxbl0xEP58bhGhtfGXuOIQTou3+lNzVdCKiz2PiDvOHEx0J+NwsDjx2E462xZAQZCjQvtSlTjTpMfUbDE3oeaQ7H3rNyw7G8yBT6LmzjUxi71Kjx0xSCCEXp9uuquqnPdGOrtyw7NwATa44Ns6Av2r4TN/H6BZo5xy4oi6EoIfDf39wsNv7pHPN+86XhiLGm537VtSFcDKcQD+/27Ztxte620dje34xZxwivGTjUMhi3upOZ8XU7dRNyMlZK9VFceWsMRBkBfe+lt710fa15Bg8+tu/m5wXu+lU1Ou3pHPBJCXXHhjM33m2jZw9V/uyQ19fLz9H256zJimKokKSZLQntLw2pboUXw8NBkOAhGh13V37lyN45t0m3RXX72ZN+YfmnFvHXQQ3R8Ax2l3bjoSE77/e6Dg3WPuXIzh4Kqrn6ZlXVoCXFfP7ZobQcLgNoy/sb3E69roYcAyDbQdOYVR5kZ73H5jyBd0J0anNK2aGsPbPnf3qBWe/XIncdBjs7UjnhvXylkP49jVDbR16jG5/1HWQOuikOvPQO7UVxX7EBBmqqurLfi6G4IU/HkRtdRmGlwQQ4SWTw6CTK4/RYbAj3uma19/vxqoPrS5YcycM1d376DfQqtIgToZ5CJKi0zYKvS50JETdkITW9+LssVChgd9T3Q8bfzTZ0XXpumXvO26nzllOzlrPzxqL0zEBFcV+RBKaA6Hd+56ZGYKLZfS7NbKi4H/+dMTWCexYe0Knj5yFw1avXy3yk2dr5CfPtpGz52o4IUKSZXAsq1//6P//7A6A2S4/nBCxZf9Jy13ta6pKerPtOTt5jvASJFnB6g8Po7a6DIOLfJi3ejt+duto2xVROh+g///89rFQVSDo5UxULaMb4YCA2+Soa5wn0OMzrKQAlYOC+MeZOIJeF05HBVtH4/ppoxD0sBBlFRcN8Ot1ngzzeHqGdiPKmIOn1ZTjwalfQGk/r/ZQJ4GtQ2RqvzLlSNnHImcdBnMyAh4O/fyutLg2+jfVCjlpiDfsPIa3dx/Hvp9OxcO/3o3511UmrbETGF4SwMFTUQAAIQQtHbxpfyf9VHmRDyMf3oh9P52q7/v0O/uwfEYIz7zbhOXv7Nffn+rIt2HnMWzYeQwHHrsJE/7zXZOcgjod0YkznWj7k8nO52YsOCUn3XFFsR+bFl5r0lkbt2tuSJLjGBf4OIx9dDP2/XQqFFVFode+nuKABxHDE+/9vG7HMSgt9GD5bTW4e2Kl5l7YRx2w8pHXSPe1CHg4hOOK6TWGkIyi3pw+95kqP1soOVp+tnTJAQ9ncXTlGKLnj0yUn01NdU+HlhdY/Xyirr/lDk6+Rk2xsd8jH95ocbyl84VU3KtxnlDgdWHT3hbcd2MRCNGsr31uBkGPvV65qjQIqMCIlPo4hqCk0AOo9nV98uhUVNdvcnQ1Tu2X383mgl12TkYffTY28yF04ZRHfe+N+lqjvshuHzsUUZuN2x11NQLgWBZ9fX9LBPPX7EA8WbZTe41l0nBCzdD+pCLo7ljdgNZI+vYay6GYPSfkTjghoS0qIBy335/i8JpPxzF/zQ5EEvbvi/CSo1tjanvmr9mBY+0JbNpzXMNAZQjVlI985CN9SKIMXlJNuDReUvuMw2A2UXJAdtuf7bHJdvk9HTFeRjhhzcNO7r8Up2r83yl3R5LuhU5jRrc/MOULeOCXu3ScXGtEcMS5HmmNOebhdNtou9Nh54z/x3g5qy59fTnyk+dkUOyRnVPe0umjEfCwGD+sGE/N6MSeUZc/I1bOuI9sgyK6d63V7W7V1kNYkcS5pCJiUnEw1LFPUrSy7dq7oi4EVVEtrwe9rF4PfW3Z9BoEvawjgs6uvVv3n7RF2ulugq/ZuDDWhSDJGrpPUqxIPIrI0VBWmsNgXJRt3ZLs3BwnVJY4tocifO5ftwuK0vW5kI985OPzR7ZxadlGydldv+9ftwtyhqSObof2uzPQfpdD2a4MjY3fxdqW31fxnwyj3bWlfVr5fhOevK0Gbo6x5qA6zY0vFa+6ac9xS36lroI+F4st+0/aYlS37j8Jn4vFfW/stHxWCmxwrsum12D55n14ZeshPJ16DGaGnLfVhXRkXpENQi61X8/MvBwMg6y69PXlyGuek6GoKkY8pC2BGJ17KJaGomaKA264WQYxUUbQqzkDzr+uUtcvU8c+ug8tkwaVSQz/wdspr01BlNfKPN4eh6IC5UU+HZmXEBWTY9/Bx29ybO/6HUcx64tD8P3XG3Wt8/6WiH5BiPAyCryd7oi8qEBRVfg9XLfb+/efaO0t8HHY3xIxuRrS5cFwXEKBT8PSvdXYjFlfHIKRD2/EJ49OxavbDuOWsRd2IvFcLA6ciibbGMLwH7yNA4/dhPveaNRlL00nIqgcFMDIh39nuxwZ5TVJiF17Pnl0qi576QZnttfXpPKa588f/ySyjZw9V43XVBr0s5oJ1rOianexeaXzmRIPQ8C52IyVn+32/3HfCYypGGBxSPy85Suqile3HcbXQ4N1zfNbjRo+NVOcbVlWEBM7nV79LhYsm/Z+XM5qnilbW1FUJEQFPjeLf5yJo6zIp+d4ml+3f9qK0EX9UehzIZyQIEgyioMe7G/RXAIPnIzq+eq595p0acaIhzbipsvK9FxtzGc0P9nlXl6UoaiA38Oi+XQcSzd14uv+/pMppvoqBwUw/AcbHbcBRP+bgJjkGD6OQVxSTPIMEGT1M5Cjkdc8n00YMTVUI0wF9C0d2pKL18VoCDmWAKK2rGeHYnp57jj85GbN9+WdRV/G8s379IncFUMG4ExcxK4f36hfMA+cDONoW9z0EKLdw3hGxz4qcbBr7+/2tOCLw/5/9t49TIrqzv9/n6q+zwzgwMAiOkEYcBPJ0Fw0IeaCRkVzQb+akWEX0b1I4pqAixCT6G7Y/WYvBiQOu3mI+t24ogkoS1T2lxhiEkliQhK5DIhJ1BEQROQyA8z0vavq/P7oPjV1OdXdzHTPTA+f1/PMM9117qdOnXO66lPvzxhTss36smMioyOj6eDcZ5ozfOHjk5Dm8JTPkXnni2d0vNedgqqEXfUVj47mrtlua8M17x+Hny7/BBgDPjP9Qqj5i8/gHE/97m3sPnwGy6+dCoDj1VXXgbGcXvNze46afdz+j9dKZfJiKQ3N//QTbF8xV1qfREbD7n+4FkDuZZcSJnqCIPpBIUnLckm9ye4yV5MU3r4jZzF+ZARNwVocO5vCviNnMet99f3OP5HRcTaR8/hWF/LjeHcaZxPZskrJqaqCuvwcWo7+GEwSGR2absCvMvgUhp5UFuNHhU25xW+/1GHeiJo4utb1gv36RTMx7+Ffeq7fMjOKoE9BOmvgp8s/4Sknd6QrgbRmYNXW17D21ulIZHR8a0EUd1/VhG37j+Gtk3FTXnf5tVPBGEP7P16LHW+dMsNEHR65bRZ+sPsdbHvtuPkioFXGTWaKkcjo0mu4miUJy8X53XoLYV/uMZRVkkbIzbS1RnG4M46RkQCWWmTT1rRMx3/8RdQmIffY4lnoTtll3IQpwvHuNB5ujUJhwOef3GWXrwv5MGfSaPz2wClXPdpao1Dzj1LEMQZ41lfIzolHSuLzg7c04/GXD+LmWRfh3mfacbw7jcfvmG3K84wbEcTqlmabLM7aBdMR9qu2sttao1BZTotSlkZIx1nTrF80E6msgRWb7f2y5tm8PF5rFP9n5gQ88etDLhm9ttYoGAN+vP84AqqC1isaXf2TzmqYM2k0xtYFpf1ncG6TwbNK5xEEUX7CPlV6rYZ95Xm0H/apnnJp5cpfNpeUs/6V6p+wTz5PhssgUzccifhVaAzQOMz1W8jV/cdfRJHK2uXirGu6MDkUnvicY2Z1SzN8jGH9opmIpTXXWrm1/SgOnIrjoVun2+TkVrc0I6gq2Np+1FyHl1vC21qj2PV2F26KXiiVvTt6JgGfwszvv+44iU99cDw+N+sil3mNYfDcu0ob95h5rFs4AxeE/TSOPCCzjTxO2SNhLpHI6Ph1R07yRya/9s3PNaMu5ENdyI+OEzGMHxmyydGIeI8tno2jZ5K46IIw/lYiEfPo4lmIpXJ3NL778gHXL72//tiknORdwIfufN3OJjN52adeE4xYWoeuGxhVE0BXPIOIX0XQr7rkc8Td6FdXXSd1iCLkc2qDPmi6gWz+0aiQhvvi99ulaeJpDSpj+H+/srdhRMiH5XmbLmu7rXfF1y+aiePdaekv90cXzwIDAwf3lEhijIFzLpWvmh+d4LoTXkBWadCfR5HZRv8hs42BodCcWq1SbyL/apXCi6U1qRTZIEuPDVmzDSB3PjiHuX4LyVUvubrHFs8GB4fKGLIGN9dhv8LwXnfaJSH36OJZBWVwnXJyCgOCfgWJjA6VMfyN5HyuXzTTJnVrDXvktpxnTDFu500bj1VbX5OOL6/x4lXnYS5hR2Yb54KX7NHr37gBX9rYjjf+5QZcP22czQX38+1HceGoMIBeiZoD/yaXgIkEVcx7+Je2cKet8oM//hPWLohiZMRv89w0MuJH2K+CMZj2V3Vj/TgVy2L99j9i7YIo3j2TQtPYWnQns1AYMApAZyyD+nG1LpslqySNTHIoreXeqjvencaq7a/hoVunI5vXq1YVhhHhIL6zaBY0Q8eoSBDvnc3ZaAuCfgV//dFLEE/3vlQwdkRI2i+TG2pMKahkRsPFF4Tx1N9+yJx0AODuq5pyMndpb5k7YXfndR7/7qqmiklOEQThptJyZgORv2wurob6RwKqfB0qo1RnH2yehzSi30W/CUlWL7m6cL4vJ3/tR/in+R/AzTMvMu2FG+sjeDO/hs1sHIWbZkzwlD60ysN1pzSMGwlwcAT9KuLpnE2yYnEdPn/6hVg571KMHxlCMqsjElSxftFM1AZ9eOtk3LSzrg35MOmruXeVbopeiAmjcmtrMqPDMLhNbs5rvHiNUZJ8pc2ziZd9m5CfSeel7Jxe7M4k0uhJ9dorCXk1l0vuvISPCG+oC2LFdZe6vPxlPMqJp7NQmOJ6PLO6pRnJjI5VW1+zHVv+dM4s45HFszzb5Wy3kKqz1umhW6ejJ6Vhw2/k5hS/evMEmsbW4cv/4/aIeM/TvY96HrnNXY+lVzehK55x1V14OlzTMh0BlWHppsL5CBm8Lzy5C49K2utVTiqjI0IbaIKoCANhM1zJ/L3m4kxWRyjQ/3kj4VH/RFpDbX9tniuYN5DbOHfG3SYz1WwKJ2T2RL+J94rEHkC2psdSWaz67Adww7TxePzlg641Uphb3PXUbqxpafZevz/7AVz95+NsaYUZZusVjagJ+sx9w33X/zn2vXMaQV+9y2xz2/5jWHHdpWhqqEF3MgsgL0E771LcuWGnzSTD6j0w4WFz7XWNkc0zSdWZyGSPxGBc3dIMzUN2SZhNiLQA95QfsoYvv3aqSxZu5eZ9pmSesxzGGAwP6aTuZNZ17K65TZ6yckJaZ86k0VAt7ZZJ1d37zF6cSWQxb9p4qYzdzMZ6V51WbN7rkreTyc7dfuUlrrZa675i817EM/Z8/vvXB6XtyWi98ZzhXuUY55nJEkEMJJWWkqt0/l5zcbZMUnsKY645MWdL2//6VzJvAEhkdWnfVLOEWVBhUC399nz7UVO+TbY3eOLXB2Fw4KYZE7BsU7t0jVz+dG793HGgEwaHdP3uSWVx04wJrrRCYnXZppyzmwdvacbya6dixea9mDN5jKv/Rfz7tuzDHVdeYtphL792qqtcp9xcxK9i3cIZtjauWzij4PHznfP7p4MFn1/FyZMxPLZ4NsIB1bR5njdtPNZsex1rF0TlXvFCPqQyOgKqgkdum4XakA+7D58wPwv5oY9NGZtzqRnyY/fhE/j41LHn9JjE+UjJGjZ2RMh1TDwK+tLGdvzp/16PRxfn7J+Onk6CAXjo1ig6TsTwtR+8ijWfm26Gy/IXHpJkYbUe3gRFGsGY2iDufaYdq+ZfZj6yqj0Hb46CdT/vwN9d1WTLZ8221/HQrTknKSNCfjz120Nme+IFTD3orjNBVA6fX8UowHYtCim5cuU/0pF/oIz5V9osJBRQsebZ111z2doF0eKJBzFvYPh5GARy48kHYM2zr5v7gDOJNO648hLUBFV7X/7kdfzo1WOmN0uxbhVaC73MP8aOCLm8DzrzrAv58A/P7cfDrbl9iJeXXxG/NuTDx6aMNT1KFjO9UBSG0TUBPHb7bJcnQa/j5zvVO9LLTDyt4Wd/PIG/+mgNFv2/37kM5As9IuQcCPoZjp1NoTal5myKhG4k50hmdBzpSphSNsmMjlhKw+vfuMH2Il+hxyTikZI1DYC8PA2w7Z6PS49t238Mut7rGWRkxA9uuXMyaUwNejIaGLyl6k7F0gj6FGl9vcxUrF4L776qCYwB913/57a7vcJ7kpdJiZdM3junky55wGRGx7Z7Po5TsbQp1SdePNx2z8fp0RNBDDDxtFbRF/riaQ0dJ3owuaEOAMA58If3utE0tq4qzELiaQ2TxtTYjk0aU1OW/IXEmnOeLGfdKylDOBjE0xpiqVy/HT2TNNePVZ/N2TNv238MyLf37qua0NRQY67LS69uQjKjof0fr7PpMZ/sSaMnlcX86Rd6mn8c6UpgVMRf0Gw0ntbwr//ngwCAPf94bVEzU1Gvv3zsd1g1/7KS1j9FYTbpumLHz3dIbSOPphnoSmQQS2dRG/S7bLlGhHwuCbq2hVH4FQV/971em7hHbstJsjnT1wZ9+JsnduLzn7gEHxg/Uioxd/Osi/CzPx7HJ98/Tir9ZrW9W9caRdbgNmkbYWtslc77r9tnI5bWXPV5Yf8x/Hj/caxfNBMZ3cCyjTmpOqdNljVcZot1sieFkZGALY2ox/d/e9hlA2a1aZbl7bR5drbnoVunw6/Y7aCtaYSs3/d++7ZZ9vXTxuGG/DiTadsAACAASURBVOOvEu3zBv1nNalt9B9S2xgYis2pMik5Xxmkrij/qqv7kFbb0DQDKU1HIqtj0+9ya9dr757BrPfVY9fbXZj1vnpXe3e93YVPTB2LjG64ZOjEWrXx94c91/bVLc0I+RWE/CoSaV26L2j9UCNUxvDF7+8paV3+3OyLEfQp+P3BzoJ1r2b79ApT0jilzXMeIdWyftFM7HjrFOZMHmOqaux46xSubGrA7re7MPN9OW9QQpLNKR8j5G1csjGLZ+HYmRQuHBWS3o1Zv2imKbwuk35zlrN9xVx89QevSp2pWCXZ9n39Oql03vpFMxH95xdd+VjLfvN4DH82MoQveKTf8JtD+OuPTsLZZAYKYxg3MmTzWqhzuaycVZ7u4dYoziSyaBpbi3fPJBHwKWioC0q9HybSGhTGTPmemqAPhzsTNic0Vlm7cCAXj4F5yv95/JIeshuSgYQ2z1XBkB2rPaksggpzeQBMG3zIS72J/F9+86RrLfjolIYhX/9YWsOv3jjhqvvHpo4ty93DPtZ9SG+ee1JZdMYyGFMbQE9Kw9gRQSQyOpZs2IVV8y+TSqiumn8ZgvkfC7L1+Jufa8bHvvmSKW0Xz+TWtZx6VE6O7nQiA4MDz+5+B4s/MhEjQn5Tjvatk3GMivhxz6Z2V96PLZ6NU7GcJJ4wM33ndBJ+lWHF5n1YNf8yU1pRJrlYYP073yGpunNBSLWMCPux7bXjmNRQZ3pm2vbaccybNh6HOhOINl4AIPeIMBhQXNIzI8J+qRxNbdCH8SNDnrZidSE/7r6qCd9akLNFfvinb2Dtgih0gyMScsvIXFwfKcnW2MsmeUTYj233fBwXXWC3w9q6913TnahTWs9Z33U/78DdV0/BtFUv5dyB/vP10A0Oxhh0zj3barVpHl0TwJlE7q3gREbHQz/J2eWJCTigAkkt92KD+JnHOaDnTU+uWfsLlwxfTdBnRmaMIRJQpfJ1wl6NIIjyUxP0QZO8QFYNUm8i/49MHm3ad6oKw0cmj66K+kcCKr60sV3qVrkcDEeb55qgD5GAD4wBW3a/g5tnXmS2c3JDjc3mWcjBTRlbC7DcmiTrDyFlm3vHRsUDz71q2p0fPZM0TSA7/uUGzJs2HnWhnB8H4Tfi2y914FuS963GjQgCgE1LWrjsfv0bN+CVQ12YMq4W67fHPeVbaf3rH3TPPo+Q9kmkNayYdylWbX0Nlz7wAlZtfQ0r5l2KdFbHpz6Yky2aev8L+PyTu9AZy+CBz7zfFjeZ0aXpE2kNn39yl2mrZEXI3jjTHDuTxF1P7capWAZLr26ypTnSlZDm47QR9irv6OmcTVdX3J335RPrTZmbnpQ8vbCtEvbJ/7Ewiq5ExuyfJRt2FUwL2CXkrO1OZXILrng0uGTDLjPPM8ksTsdz5bx5PCbN/3BnAp3xnK3ZnU/sxNHTSWm8RLp63wwniKGOltVxJqXZr9+UJt1Q9wWvuU3Ye/YXLasjrXFb/dMaL1v9Ex71T5Sh/kJ6zJV3pjr6fqDRdQOxlIYjXQmkMropPdeTytl2dzrXqesuzdk5Z3X05NMVWuvEurRi3qU42ZPG1Pt78/nvO2ajK5HBtv3HcPR0Cnc9tdtWzqlY2pa3VXrOGm/+9Atta7Moz+tclWssnK/Q5jmPkPZJZnWpnIyXVJ1Tki2R0aTp4+lcPJmEUFtrFE/8+qBESg3YcaAT92xqx+0fucSWZlTEj4dune7Kpzak2o6pnpJFMNtwx5WXuPJ5vv2oecyZ3irhJyTvrpzS4OqfJ359EA8XkMkrJiGX1NxySPc+0ytf9+2XOvDgLe66rX3xDSzd2I7TeYkghUHeBzT6CaJipD3mzHSZpN4qLVVX6fpXUk6u0hJjfo++91epCkMiqyOZ1VEbUqFzbkrPPfHrg7j9I5eYZhNWWbg7rrwE3cksnvj1QdQEVNe5fOjW6eZaJ9allZv3IaMZtnxmvq8eyzbKpe7u27IPYb9qW+tl0nP3bdmH5ddONdfmh1ujZnkqYyQ3VwGq9xlLmRHSPl6SdMVk3AT1NUFpvDF1uccs4YCK+x0SQvU1Aaz7eYcrjfWRT13IZ3o3FPbAq7a+hlXzL8PkhhrE0hpGhP042ZPGY4tnIZJ3pe0lWSSk3V451IXaYG/ePUkNQR/Dog9PxI3RCa76CtsqYessJO9ksnNOWblkRgMYw9oFURw7k0Sdh0lJJOhDrIDEnOhzYefslBe8+6omrN/eYcb7s5FhPPXbQy7vkLfNmegxGgiC6C+VfrRPUnXeVFpiLOBX8cLOI8NmThUmG0/99hBumzPRNC/8dN400UumVZhEdJyM477rL8Vji2cjElTN93PE+rjmJ6+bZhViXbfmU0jqrjbkg09hZt7iuDNe4+gIDJ3jllkXoSag4uHWKI6eTiKYfyGx2FgwDI5EVidJuhKhzXMeIe0jTAGcsi7C25CXJJtAPL7xkl+LSSSEtq+YW1Syzenlb9X8y3C8O41vv9Qh9VT4wHP7cbw7jUcXz5JKFlnzPtmTxj1Pt2P9opmmJySOnKD7Nz/XLE2/9tbpuPLBl8xje79+nbQNb52Mmy8HipcuHrt9NjiAw53yvoqlciYu3/xcszT8RHfK/L5177u4/9Pvx5lkxvUW86lYGgDw3tkkPvn+cTa1ktUtzUhldUTK4CmMIAg3lfZyp2V1nHUqILVGMQpAoAzX9UBI1VVSTq6SEmPxtIYf7z+Or2/9g3lszqTRuHnmRVUpVRdPazAMjms/8Gcuz4Lvnkl67gnOJHJxt+591/bS+qr5lwGA6yVD67ouvsfy48xLyk54zxVj/DuL5F52D3cm4FcVBP0K7tzQG79tYRRjaoIFx4JhcHTGM1i6sVfRw+mFkLBDD67zCPOGbfuPSU0Bnttz1HX8oVunY1TEbzs2UmJOYTVVkD3uqgmoWNPinebh1iie+M1B22MdYbLg5alQeOmTedyz5r26pRk1wdwjp+fbj5qPDcVjIS+Th7qwvd2ydlnLsZp68LynxLUvvuHq07aFUfx33oTFs+yQveywX5WayoT9ORMWL89OhlF8XBAE0Tcq7eWu2s1CKp1/JYn4VWndq9UUQNxlvfeZvXhuj92zYMCnSMfxc3uOSs012hZGsX57h9QzocjXurfgBvfcezwsMel84jduL7vCLETm3XfZxuKeHxNZHUs37inohZCwQ7fd8ohHaHfNbcKFo0Lm46g3j/c+ctl9+AxWzb8MU8bV4s3jMXzzx3/CQ7dOx2OLZyEc8KHjRAx1QR/+KW9OIeTXGIC1C6LoTmYR9Kt4ZucR09Sg40QM//eHfwQAM2/hBXDtgqhporHO8fhI/MoVHoesWBUthMc90ywjpSGj6Vi7IJprW/4xoaIw3DZnIlJZHSF/r7rHn40MuzwDijTf/FwzJlwQxpvHYwj6VWzedURaTndS7q1RvAnea9ahIxxQTBOWQmWvXzQTdSE/khkdkaBbjUQ87hKPquTmIdU50RNENVDtXu6E11mrWcjhzjjG1I2sivwriaoqGF0TsNU94lerVjdYVRXUKAyvHOoy7+je/pFLUBtSwRjD8qfbbevUA8+9iufac3sCq7nGyZ40RtcEsHZBFD1JDSFfr7nF0dNJ/OjVY5g3bTzuvnoKkhkdX3v2VXxrQRRf3/oavnHTBxHyK3h08SxE8vuJ0RKTztxeoMm2h7CahThNSZ3eBGV4rpFF0p3P0OY5TyKjm96eGGM43p1GWjNsj11mNo7CuBFBcM4xfmQIa2+NIp7RoCrM9Eq47Z6PSx/FCW3j7SvmujzgCU72pG0ayI8ungXGmPnmtPOxzta972L5tVM9TT7mT78QPaksFn14IjpOxEwdaafWspj4FMYQCeTsjYX3KMaAe66Z6tJS7k5m8eX/2YdHF88yba/PJrI43p1GXciP986msG3/MSy4ohFnElnUjc09yhMetJx1BgAOjqxmmJ4M3zublPblm8djZt0fu3222T/OPkhldAgd850PXIPn9hzFqv/9gxlOHgYJonIMhJe711Zdh4xFRzqgsLLm/40f/qmiHhLDjs1JOKBWjZc+VVVQl98sV0N9i2Fdl1b97x+w+/AZfOOmaUhmddxzzVRTFm5MrR/3XDPVtGd+8Q/HMffSsWgMRpDM6KaPg9pQzk+BIKAq+Oz08Qj6cnJ4HBxrW6ab14nwamjVlPbyjttxIg5AbhYi88pbbK3zWkNpjfSGnKTkkXpMsngQFF7qNv3e7TVvXd4D4Bee2i310uf0qpfKGnjmlcLe99pao/jDsbN45BcH8djiWUhkdGnZXl76ZN6MrJ4MreUID0TC45CuG+iM2/vCWbddb3dh9sTRqI/40ZXIYuehTpcXI1ndhBeqrkRG2h6r90OZh0FrPYRNFufcVd///IsZ0POPdWV5F7HnGvTnpuQkpf+Qk5SBgTwMDs38hyBD2kmKphnoSmZs3nZffeeMbV1benUTWq9o9Pwu9g27DnVh9vvqkdYNl7fgTb87jHU/77B5KbzswlF4bs87uGnGReb/+7bsk+4n2lqj2PT7wzhwKu4OWxiFwmBbM9ctjGJ0TbCg7TLZPNsgD4MyCnnD8vKYxDnAGAp6Gnps8WyA5R5/pLI6DAO2t25DARXdySye23MUuw+fwT/feBlq86oSdSG/zbvem8dzHoDmTRtv3mF9/I7ZyBockYCKeDr3a/DNvKegJR+fhKzl7ovKGAwO3Llhp6ue37ltFvyKvT6r/vcPtjsqwtuirI0G54j4VSQ1HTUBHxSFwTA44hnN1X9eXhAfXTwLj798EHdceUlB74dWb4G5vtShKMi5MrW8DRxLa/jur3IeBKeMq8XhzgQuqAlIPSOKu/lF3iQe9NmCNs/9hzbPA0OhOTWgMNed4UwVeRjsONGDyQ11qA35EEtpeOtkD5rG1lVF/YcgQ3rzLDxKXtnUAIUx3Llhp2u933bPxwt+B3rXsDOJrHT9E099rd+//VIH7r6qCZMbapDMK170pLT8U9wkfIqChhFBJNI6fAqg5fcXtr1GRkfYpyCtG5b9Ry6vUjbApLZhMnw8DDLGLgawAcA45HzHPco5b2OM1QN4GsBEAIcA3Mo5P92XMgrZzz25IydfM25EEFPGyeVkxOCV1B5AbmACwG1zJmLO5Jy024rNe3HX3CbUhfymd72Hbo1i3sO/hE9huPvqKWb+Ab+KAICp97/g8hr1xU9OQSj/Eo6YdA3O5XbAwdwjI2c+oq26bhS0EX7zeM5j4toFUfPFH0Vh0v7z8oIo5H2++Em5BNCIsN8W1+xXBoR8OfMS66MkqwfBt/71U7hm7S/wxr/c4Fl2uV5YIgjCm5qgTzpfVYuXu5qgDy3f+W1F6y/zRlvNXvqqmZqgz/Qu3DS2xnwHyTrGnHJyXvJyI8J+1IX8Bd9HAnKeAieMCpuehb/3u7dxy8yLAeReuGUMqA36oRk6xH3OgE9FKL+ptapFiTUxYrE7rw2VPpYqqc4yHKmWZ0MagHs55x8A8GEAdzPGPgDgKwB+xjmfAuBn+e99wssLz+HOBG6YNh6ZbM5zoJBXc8aLpXJ3a5c/3Y6ueAZ3btiJqfe/gDs37EQim7NpsnoO6oq7vROumHcp3jubNPO0yskdP5tCzMNjn2zT7uVhquNEzJTicYZlsjo64xnPNr55PNbrBdDxFq6sPC+vS6KvveohvBta+3Xq/S/gzid2ojOeMX+IyMoWduFeeVerByyCqDYq7YWu2vNPeXijTZHntwFH1w3zfGzbfwydsZzHv56kfQyI9cXrO9ArL1fM66DMU+AN08bjV2+ewNHTKXz+yZxnyy88tQu6ATz120O4c4N8DSQGnqo022CMPQ/gP/N/cznnxxhj4wFs55xfWiit16ObTEbDGYdm6IO3NGPNT17HyZ6cXvKSDbvQUBd06SoLG6S1P31T+hjHy3zh327+IOau2W479s3PNePL/7PPZtu7uqUZDMCWXe+g9UONNhtiL7skmQ2TsHn+649egkRGd9nahQOqZxtFX4gXDh9bPNv2q1ZW3vpFM5HI6Lj3mb02m+UxNQGcimdc9mROu2RhH7b2p2/a+uix22fbfhlby/ayVRN5C7vuIgz6relKmG1UuxlGpalSM48hO1Zlc2pbaxSjQr6y6DBXOv9URkO3JP8RIR9CZcg/lsriTonZxmOLZ5VFB3sIMmTNNnpSWaSyOpZubDdNNVbNvwzb9h+zvZdTis3z6pZmRPwqdIMXtHn+6fJPSPcFwt9CIXNG5xpIlJXhY7ZhhTE2EcAMAL8DMI5zfiwf9B5yZh2yNEsALAGAxsZGab5CNshL/kU8IpTJq4X8vfJqssc4XuYLMkmZCReE8c3P5TbLpneivEdAU6KmBK9RTg9TQvLurz82CRG/irBfdckMsbxUj7WNQpZP9IWop1PmTebRKuxXzEnIKVW1ZltOFrA+EsAjt81CbShXD39eMu+WWRcjbOlXax855XOcZaeyOj42Zawp+1MtUkqljFOCGAqUOqdGDMN2DTLwsnkArLSHwUp70Yt4mJ1EaFNUNkqdU4WHQaunP+FhsONk3O4ROBIw18ZEWseW3UekaxznHKmsYZOxG5H3zvvFT/aaZFoRJh/FzBlJQm7wqaqrlDFWC2ALgHs4593MYrvKOeeMMeltdM75owAeBXK/PmVxEhkd3/jhn/Do4lmm7JzAamrglFfTDAOd8d4wmZcgL6+DVkmZ+dMvxPJrpwIAdINjtUMa7r2zSfx0+SdEe2x18DL0Nwxui8uNnBi8iMtyejmmnXRPqteLovCYtH3FXKkcjngxMSQ25vmNqdVmSuZNUUhVyY4/dvtshAI+85FUMmOULJ9jtdey2oFVk5RSKeOUIIYCpYzVeFrDyZ40GupC5rETPWk0gJVN6q2SL9zF05pNfvN4dxpnE9mySuFV0oMhUfqcGk9rplmkWMM7TsRMydamsbV472wSI0I+KCrDn40MgXMODo6ziaxrLRNeAQs9bf7Vl6/y9Fwo9TSY1Ez7+HhaM1/YJwaHoXsbzgFjzI/cxvl7nPMf5A8fz5trIP//RF/zj/hVrFs4A4DbI19baxRhXy58+TVTsOK6Xju1u57aDcaA7yyamXu0sr3D5XGoNuT2ILhuYRQX5L0T3hS9EF++/lJ89QevYur9L+CrP3gVX77+UtwUvTAXtzUKxhi2th/F0dMpLNmwy2IDnEZPKuuyCxYySCLukg270JXIIJHxtiGWeY0aFfHjWwvc3owef/kguhIZLH+6HUs27EJnPANdN6R9am/3jILHhQnGnU/sxAPPverqSxGPIIihTdinojbot81BtUE/wr7yXL9hn9zLXTnzb72i0WaT3HpFY9XUnyidsE9FOO8tcNv+Y1jTMh0HTvaY5//eZ9rBASx/Zm/ODvnJXTh6OoXHXz6I1isasfyaKTbvg5xzc0/gteaPCPuk5//gqZjb825rFAA3x6JYc8n2efCoCptnlrvF/ASALs75PZbjqwF0cs7/nTH2FQD1nPMvF8qrkN2TkFx7+c2TmDN5jPmobsdbp/CxqWMR8atSSbZCUnWHOxNY++IbAIC7r2pC09haJDK5X41Azi0mPGTlHls8GxwcDMCdBWTyZLbTwkbby27KVo7FfkrXDSSyuvkYNOxXkdEN6AY3vR59+6UOqbMV2R2fQnfFZcedMnnijnzj6MhAyucM+s95snkeeMjmuW/0Rf6zXFJvJ3tSaKgLmfOV+F4NUnI9qSwef/mgeWezIy89+lcfvWS43nkesjbPYt1pqAvm1+kaxDM6Pp8//16SdGJNtnok/vZLHTjZk7btCcTaBfSu+adiaWxtP+o6/4s/MhF1oZzKlBjXfoXhr/5bskcg2+dKMKxsnq8EcBuAVxlj7fljXwPw7wCeYYz9DYC3Adzan0KE5NqXNrZL5YkUJpdks0nV8V6zAYNzXLP2F9AMjvnTLzTjM/RKvNUGfZ6ycpFgTpZNhHvJ4shsp631nD/9QnPjnszomD/9Qrv9ssV+SuY1yqcqMDiXytsJ2Z1SJKIUljOPiQTzpiN+ueyctY1b976LH716zFMeirQpCWJoUmkptpqgD//wXAfumpub2949kzJlNMuVf6Wl8A6cituOHTgVrxqpuuE094p1RzM4tu59F2/966dQE+g9/5Mbamx2zd9+qQM/evWYuSbXhfzgHKb5hk9h5ntBQn9Z9BUAhAMKLq6PmBKrAp/C8HdXNSGZMUyZ1pqAD2By+2iyfR48quIq5Zy/DO9fA58sZ1mJtIebyrSO2vyvQVm4kHGzql+IuDL1Clk8L9teUSeZPbWXO05hT+elnAHkNqaluuD0ss+zyuk5bfVkKhjWN49lSiHn0r/kFYkghi5C+svpbTWV0cvyUlyl86+0TXKl619Jhtvc61x3Ok7EEPQp5hraGc9g1dbXbGtoU0ONuSYf6UogrfWaLQqZ22vW/sLTC6Guc9f4Wnp1E7oc3nLXLYwiEvCV/P4PMTBUjc3zQKEocNnZrm5phpLvKZm97oO3NOPbL3Vgx4FOLN24J/dYxhJ3+bVTcd+WfdhxoBOawT3jedn2ijpt23/MZQtltaOyphX2dLKy79uyD3df1XRONsQye+jVLc1Yv73DtMly5pPI6li6cQ92HOjEXXObsHKzdx9Yyym1f635F8qTIIiBx+Dcdc2v3LwPRplMBSudf6Vtkitd/0oy3ObeiF9F28Lec71t/zGMivixuqUZy6+dins2tbvW0Ns/cgm27T+G1S3NGBXxY9v+Y+Y4+daCKNa++AY0g2PetPFY5ki/bGM7RoT9eOhW+7tQt195iSvu0o3t6E5m3XbQC91rLjFw0E8WByG/ijXbXpdKzwBuWTSpjFtAtcUdXRso+MhFJvNmfQQm6nTX3CZcOCqE9Ytmoi7kRzLT+xhIlrY+EsCYOiYte8q42lyaEh+1qaqC0TUBmyyUyhjWLoh6ysBZTTC8TE6Kyc4V6l9PT4j0KIsgBp1KS7FVOn+fT0F9xD7nhX0qfL7y3HOqZqm64Tb3inXHuu4/t+corv3AODSOlkvN1oVzsnMKA1QGU4IukdbwwHP7zTXLa+0LB1QwBjy2eBYi+SfMkaC8X8eOCOHvn2631a9a7/IPF4b+VTqAiBcGhb7y3z/dbr4YJzalVrulVFbHtv3HcPdVTaZ7zW37j9kepXDOvc0y0nruhYL8BtbpGtNqU3bPNVOx1iFf9193zLbVB9wuRZfSDUBD2R73yOyhnZ+tWNvtZXJSSHYultakMnmmOUsRcxeCIAaPSps9JDI6Nn/hw5jcUIfakA+xlIa3TvZUzfVfzfNXNdfdi2TWwKqtr6GhLoiV8y7F4o9MRCKtFxzHwi4ZyL0A+NUNr2LV/MtwvDttxhUysxfXR/De2SR8ioKGEUEk0joUJfeOlMJYbgx7lHWkK2HKxwLWlwX7/kNuONmsDwZktpFH2HAt2bCr11XqdZdi+TVT0NYaRUhVTAk1IfMWT2tY/JGJEimjXLfquoHOeAaPv3xQKj2zZfcRT5fTVsk2mXzddxbNRDxtl53rSWXRGU/bjumGgXULo54mIZXEaoIhk/ArVo9i5izFwgmCGDwqbfYQUhVMGBUx3Rh//sldmDAqglCZHCF5yX1qmlE8cQlU8/xVzXX3IqQqWL9oJr5yw5/jy/+zL7eGbtiJtKbbTDrEOH785YO2vcCY2oDLvPKm6IVgjOGrP3gV9z7TDsYY7nm63cy7K55BTyprk4t196vcNLM/fe3cX3jtQwhvqkKqrpx4ydU4JdKAXmm3Db85hL/66CVS2SKZTJyQj7FKHVkVL3pSWWz4zSHMmzbelHlzSs541UfI38jk7bzcgP/XHbNhcAzKL0zrr1urhF+p9Sj267hCv54H/ec3SdUNPCRV1zcKSdVpug6fqppmD+J7tUjJVTJ/oLrv/vWh7kNWqg7Ine9YSsPyZ/a6zvnDrVEEfQrqQn5z/baqZIi1WVEAw8ipaSQyOhiYuU57yd39280fxJi6oPSJs1PirlzjxHN/QdJ3wDCTqqs4XjZcdSE/1v28A1/85JSSZeKEGYVV6kg8cvEpDK9/44a8q+0prjTF6uOUr7Pi5QY85O+V0RvoC8PL81+p9ZCZs5xLOEEQg0NN0Iep978olf0sV/6VlpKrZP5Adc9f1Vx3GVYX3VZeOdSFMbVBAMDkr/0Ib/3rp7Du5x2uOGJtFtSFFNs6XUhq1pLMs1/L2dfDzWZ9MCCzjTzChsuKVR5O2D05w2UyccIGyiuN1f2nM02x+oh4snDhBtyZ5s3jMXosQxDEgOI1/8XTGuVPDDniac1zDT3SlUDHiRjmT7/QdOPtjONcwwH7Oi3WfVnesrSVpNj+gigObZ7zeEmkbdt/DG2tUaiMuWx2H7p1OkYVsEWSybuJPK0ybzL7pb7Y+14Q8bvsm71k3giCICpJpW2eAwqT5h8ok9lDpfMnhhYRv4pREbd8nFWK7u6rmvDEbyTvMHnIxjnf+5HlfUHEP+C24sPRZn2gIZtnC07X1Fb7IqYwLH+63fRmJbxlPXTrdCSzhqctkizPZMaAosA0p/CyX+qLvS/QaxslXIWKN3StnhKJggx6B5HN88BDNs99o9BY1TQDSU2viNSbwTl++cYJzGysN9U2dh/uwsenji3LHFfp/M9DhrTNM5AbrxndgMG5KR93NpnBi384jjmTx2DKuFpMvf8FfOqD4813mDpOxNA0tgaqIh/X7vd+evNWFCDkGxw792q2t68wZPN8LhgGR1ci6+kxKZbWcLw7bbrfBHIG9smsUdAWSSbvVhvqvcgK2S/11d63FJk3giCISmIYHKeT3nNqf0lkdDzyi4PYcaB3QzRn0mjMnji6LHNcpfMnhhbW8bpq/mXSl/seXTwLl0+sPyfZOM/3fkKDO4aGm836QENmG3mKeUyqtscc1VZfgiCGF5X2QlfpOY7m0PML63j9e9mNmAAAIABJREFU9ksdEm++M2hMECb0cyNPsbdPi3kBHGpUW30JghheVPqN/krPcTSHnl9Yx6u4q7xq/mWYMq7Wdu5pTBAA3Xk2KeXtU/GYQ2H5/0P8gqm2+hIEMXwYiDf6Kz3H0Rx6/uAcr1v3votVW18zTR3FuacxQQB059lEPI5x2ufR4xiCOD841xcqq/QFwwGD5lSimqDxSpwLtHnOQ49jCIIgygfNqUQ1QeOVOBdo82yB3j4lqgmSniOGOjSnEtUEjVeiVMjmmSAIgiAIgiBKhDbPBEEQBEEQBFEi9FyCIAiiD9ALhgRBEOcndOeZIAiCIAiCIEqENs8EQRAEQRAEUSKMcz7YdRhQGGMnAbzdh6RjAJwqc3UGE2qPN6c459eXKa8+0Y9xei4MtzFwLgyXtlfLWK32/q7m+g+Vug/qWC1hnA6VfnJC9To3+luvksbpebd57iuMsZ2c89mDXY9yQe0hzuc+O5/bPhhUe39Xc/2rue4DyVDtJ6rXuTFQ9SKzDYIgCIIgCIIoEdo8EwRBEARBEESJ0Oa5dB4d7AqUGWoPcT732fnc9sGg2vu7mutfzXUfSIZqP1G9zo0BqRfZPBMEQRAEQRBEidCdZ4IgCIIgCIIoEdo8EwRBEARBEESJ0OaZIAiCIAiCIEqENs8EQRAEQRAEUSK0eSYIgiAIgiCIEqHNM0EQBEEQBEGUCG2eCYIgCIIgCKJEaPNMEARBEARBECVCm2eCIAiCIAiCKBHaPBMEQRAEQRBEidDmmSAIgiAIgiBKhDbPBEEQBEEQBFEitHkmCIIgCIIgiBKhzTNBEARBEARBlAhtngmCIAiCIAiiRM67zfP111/PAdAf/RX6G3RonNJfiX+DDo1V+ivxb1ChcUp/Jf6VxHm3eT516tRgV4EgikLjlKgWaKwS1QCNU6KcnHebZ4IgCIIgCILoK7R5JgiCIAiCIIgSoc0zQRAEQRAEQZQIbZ4JgiAIgiAIokR8g12B/sIYOwSgB4AOQOOczx7cGhEEQRAEQRDDlarfPOe5inNetldpDYMjkdURCahIpDUojCEUUBFPa4j4Vahq4Rv2tvQZHRG/CkVh/QrnPHesJugruR4CTTOQ1HrThn258mR1kJUNwDwWT2uIBFQks0ZZ2mUNJ8pLf/tb1w1zzGWyOrIGN8eQWuSasKaNpzX4FYaAP1ePsE9BUjMQCahIZXUYBhAJeo9DrzjlbGtf0tN4Lp2JX/nhOcU/9O+frlBNCOLcMAyem4N4bg5KZXTonNvW04xu5OLm4yTSGnwKg8Gtx3SE/b1zX6XmMmJgGC6b57JhGByd8QyWbtyDVw514fKJ9Vjd0ow1z76O491ptLVGMbom4LlxlaVft3AGRtcEzE3BuYY/tngWEhkdyza1m8eK1UOgaQa6EhlX2hEhH+58YqetDvURP7oSWVvZ31k0ExndwNKNvekfvKUZz+15Bws/9L5+tcsaTpSX/va3rhvojOfGzfXTxuGGaeNtY6jQNWFNax1zL+w8grOJLFqvaMSyTe0YNyKIFfMuxcrN+zzHoVccazv629a+pKfxTBDDH8Pg6Ell0ZPWsHLzPul81LYwiqBPQU9Kcx1XGPCl79vnwU2/P4x1P++oyFxGDBzDweaZA/gJY2wXY2xJfzNLZHUs3bgHOw50QjM4dhzoxMrN+3DX3CbsONCJZZvakcjq55R+6cY9Zpq+hGsGx7JN7bZjxeohSGq6NG3Wkre1Ds6yTyeyWLrRnv6+Lfswb9r4frfLGk6Ul/72dyLbO25ujE5wjaFC14Q1rXXM3RidgHn5TfiOA524a24TVm7eV3AcFopTzraea3oazwQx/ElkdZxOZM05SDYfLdvYDs4hPR5L6a55cN608RWby4iBYzjcef4o5/woY2wsgBcZY3/inP/SGiG/qV4CAI2NjQUziwRUvHKoy3bslUNdaBpba36uCXp3m1f6SEDtc/iIsF+aplA9BDVBX0lpxTFn3IvrI5790d92WcOJcxunxehvf1vHgtf487omvMbciLAfdaHevMQYcsazpveKY21Hf9val/Tn+3gu51gliErR33EaCai2NdBrPvKaIy+uj7iOiXlTfC/nXEYMHFV/55lzfjT//wSAZwFcIYnzKOd8Nud8dkNDQ8H8Ehkdl0+stx27fGI9Ok7EzM/xtHbO6RMZvc/h3cmsNE2hegjiaa2ktOKYM+6RroRnf/S3XdZw4tzGaTH629/WseA1/ryuCa8x153MmuMGgO2zNZ41vVccazv629a+pD/fx3M5xypBVIr+jtNERretgV7zkdcceaQr4Tom5k3xvZxzGTFwVPXmmTFWwxirE58BXAdgf3/yjPhVrFs4A3MmjYZPYZgzaTRWtzRj/fYOzJk0Gm2tUfMlulLTr1s4w0zTl3CfwtDWGrUdK1YPQdinStP6LXlb6+As+4KIH+sW2tM/eEsztu0/1u92WcOJ8tLf/o74e8fN8+1HXWOo0DVhTWsdc8+3H8W2/cfMsPXbO7C6pbngOCwUp5xtPdf0NJ4JYvgT8au4IOI35yDZfNS2MArGID1eG1Jd8+C2/ccqNpcRAwfjnA92HfoMY2wScnebgZwJyvc55/9SKM3s2bP5zp07C+ZLahvnvdrGoFeqlHFaDFLbOC/UNqpirJLaBoFBHqt9nVNJbeO8o6TOrmqbZ875AQDTy52vojDU5m04a0N+83id5XPJ6SV2yX0LZ6jLb1BKrYfA51NQ53OnldXBq27is0hfG3Rv3PvbbqK89Le/VVUxx1wo4EMof7yuhGvCmlY65vJhkYB7jDnr7hXHSn/b2pf0NJ4JYvijKAwRy/Vt/SzmNp/Pvh7WSubF2pB97qvUXEYMDFVttkEQBEEQBEEQAwltngmCIAiCIAiiRGjzTBAEQRAEQRAlQptngiAIgiAIgigR2jwTBEEQBEEQRInQ5pkgCIIgCIIgSoQ2zwRBEARBEARRIrR5JgiCIAiCIIgSoc0zQRAEQRAEQZQIbZ4JgiAIgiAIokRo80wQBEEQBEEQJUKbZ4IgCIIgCIIoEdo8EwRBEARBEESJ0OaZIAiCIAiCIEqENs8EQRAEQRAEUSK0eSYIgiAIgiCIEqHNM0EQBEEQBEGUyLDYPDPGVMbYHsbY/zfYdSEIgiAIgiCGL8Ni8wxgGYA/9jcTw+CIpTUYPP/f4CWHW8MSaQ09qSwMztGTyiKVKZ6mWHmJjIZYyh5XhOuGYZZXKJ6sbrpu9LuvUhlHnoaBWEpDIt9u85ikjUXPgyWfQumL9SXRP7zOdyKtIZb/bD1X1jjO8aFpRsFxDQCaZhQto0/jyZJG142yXAsEQQxfdN3Iz0G9a611zY2lNCTSuXlJ1w2kMpoZPxeeRUKynom5z5qXyNs6L3rNkZVc80rd65zPa61vsCvQXxhjFwH4NIB/AbC8r/kYBkdnPIOlG/fglUNduHxiPdYtnIHRNQEoCisYDsAMGzciiBXzLsXKzfvMeG2tUbyw8wh+vP+4NE2x8mR5rlsYRUBV8MRvDuGmGRfhvi37Csb7wlO7Pes2uiYAVS39d5S1btdPG4cbpo3Hsk3tZp4P3tKM5/a8g5tnXYQ1217H8e60eWzhh95ntrHU87C6pdnMx9pHpZ47on94nW/ZeFrd0oyOEz34wPiRWLapXTo+2lqjMLiBB559XTJeZ+CCsB9diUzBMgqNB6+6e5XRn2uBIIjhi64b6ElriKU1/GDXO7hpxkV4bs875pprnZPqQj4YBoeW31y65qxnc3PW6pZm/OyPx/HJ948z87TmtaZlOoJ+hi99Xz7/rVs4A/URP7oS2YqseaXudc73tXY4rBIPA/gygH7dNkpkdSzduAc7DnRCMzh2HOjE0o17kMjqRcOtYXfNbcLKzfts8ZZtaseN0QmeaYqVJ8tz6cZ2nE5kMW/aeNy3ZV/ReIXqJsrsS1/dGJ2AZZvabXnet2Uf5k0bj5Wb9+GuuU22Y9Y2lnoerPnI0hfrS6J/eJ1v2XhauXkfZjbWm3Fk42PZpnbUBP0e43UPkppetIxC48Gr7l5l9OdaIAhi+JLI6jiTyGLl5n3mWmtdc61zEueAZnAzvtectXLzPtwYnWDL0xp3xea9iKX0Amv6noqueaXudc73tbaq7zwzxj4D4ATnfBdjbG6BeEsALAGAxsZGaZxIQMUrh7psx1451IVIQC0pXIQ1ja2VxhsR9numKVaeV54X10dKKlvE8wqvCZ7bMLDWbUTYL81TlNU0ttZ1TLSxWN7O/MRnZ/pi56ZaKGWcDgZe59trPNWGfEXHR03QV3A8Fiuj0HjwqrtXGc7jRHGG6lglCCv9Hac1QR8iAZ9rTSu0xteFvNdEa9xCeZWyZldqzSt1r1PucquNar/zfCWA+YyxQwA2AbiaMfaUMxLn/FHO+WzO+eyGhgZpRomMjssn1tuOXT6xHomMXjTcGtZxIiaN153MeqYpVp5Xnke6ErawQvEKhcfTmrRPvLDWrTuZleYpyuo4EXMdE20slrczP/HZmb5YX1YLpYzTwcDrfHuNp1hKKzo+4mmt4HgsVkah8eBVd68ynMeJ4gzVsUoQVvo7TuNpDUe6Eq41zWuN705mzfjOcOucJebF/qzZlVrzSt3rlLvcaqOqN8+c869yzi/inE8E0Arg55zzRX3JK+JXsW7hDMyZNBo+hWHOpNFYt3AGIn61aLg1bP32DqxuabbFa2uN4vn2o55pipUny3PdwiguiPixbf8xPHhLc9F4heomyuxLXz3ffhRtrVFbng/e0oxt+49hdUsz1m/vsB2ztrHU82DNR5a+WF8S/cPrfMvG0+qWZuw+3GXGkY2PttYo4umsx3idgbBPLVpGofHgVXevMvpzLRAEMXyJ+FWMivixuqXZXGuta651TmIM8CnMjO81Z61uacbz7UdteVrjrmmZjtqQWmBNn1HRNa/Uvc75vtYyzofHm5J5s40VnPPPFIo3e/ZsvnPnTmmYYXAksjoiARWJjI6IX3W9mOYVbg1LZXTonKMm6EM8rcGvMAT8hdMUKy+V1WEYQCTYGxfI2SeF/QoSGR01QV/BeLK6Rfxqn16QstYtk9WRNSx5BlQkMwYUBQj51d5jWcPVxqLnIa2b+cj6qNRzd44M+psPhcbpYOB1vlMZHQbniAR9tnNljeMcH2GfipRueI5rRWHQNANJTS9YRqnn2Wts6LqBRFbv97UwyFTFWJ34lR+eU56H/v3T/akSMTQZ1LHa1zlV1w2kNQMGB8KB3For5pIaMScxAAwIqgqyei6uwfPzWlqDwhhCjvVMzH0iT+v6mdYMc170miPLvObZKHWvU+5yhwglNWbYbJ5LZahtSoghyaDPBDROiRKpirFKm2cCVbp5Js47ShqnVXebhSAIgiAIgiAGC9o8EwRBEARBEESJ0OaZIAiCIAiCIEqENs8EQRAEQRAEUSK0eSYIgiAIgiCIEqHNM0EQBEEQBEGUCG2eCYIgCIIgCKJEaPNMEARBEARBECVCm2eCIAiCIAiCKBHaPBMEQRAEQRBEidDmmSAIgiAIgiBKhDbPBEEQBEEQBFEitHkmCIIgCIIgiBKhzTNBEARBEARBlAhtngmCIAiCIAiiRGjzTBAEQRAEQRAlQptngiAIgiAIgigR32BXQMAYmwpgJYD3wVIvzvnVBdKEAPwSQDCf5n8451+vcFUJgiAIgiCI85Qhs3kGsBnAdwA8BkAvMU0awNWc8xhjzA/gZcbYC5zz3/alArpuIJHVURP0IZ7WEAmoSGYMKAoQ8qtIpHUoChBQFCS13ngqYwgFVDNNOmtA59wWHvApSFryDigMPp+CRCZ3LJPVkTW4Ldzv780zqxm28EhARSKjQ2UMQX9vPvG0hqDC4POryGZ1ZCxpwj4VumHYjol8/ApDQJIm1wc6FEsbw34VGc3dRmu4pufqK/J3xpOVk84aMDhHxFG3iF+FqvY+JNE0w9b/zr5y9r/0mCPP4YhhcCSyeq4f05p5DlMZ3ewL63Hr2BHjRfRzKqOb58aZl+y48/yK8eXM1xkmPmtZHWmP60GMIWfdbWPQUYa1XaIM6zXnvP5EnFRWh2EAkWDvWFQU5u5fRxhBENWNWGec8yAAGDw3J3jNf7b1S+wjGKAyICvmk/w8k3HMc+K7fZ7WoTAg6FeQzBoI+xSkdcOcm6xrtU9h0AxRJ/mexa8w+FUFSc2wzV8Acp+DqlkmGBDM71Ws63kircOnwJw3rfFD/ly8kKq49hxhn4qUbpR93hzo+XgobZ41zvn6c0nAOecAYvmv/vwf70vhum6gM57Bsk3teOVQFy6fWI8Hb2nGc3vewc2zLsKaba/jeHcaj9w2E7GUZou3uqUZa57Nha9rjSJrcNz7zF4z/FsLogj5Fdz11G7zWNvCKHxZhru/twfXTxuHG6aNt+XZ1hrFHw524pFfHMR3Fs1EWjOkdfuLDzfidIJjxea9trRBTUda47Y06xfNREY3sGyjO5/WKxqR6kkh5Pd590G+jesXzUQqa+Dvn5b3QVtrFJGAisdfPoibZlyE+7bss8U7eyqDhrqQrRxZv1nrNromAFVVoGkGuhIZz75a0zIdQT/Dl77fGy471tYaNfMcjhgGR2c8g6Ub99j6/me7juOT7x+HlZv3eZ67kydjCAdU1Ab9WLapHeNGBLFi3qWuNF55yc5vW2sUL+w8gh/vP4621ig2/f4w1v28Qxo2EsBZxzVmPcfW+so+f+WGS5HM6K70qZ4U7tuy32yjqGOh669pbJ2tfesWzsDomgAAuPpXhNEGmiCqG7HOxNJZ1Ib8WLYxNw8+8Jn3I5U1sHLzPs95UcxHYv26acZF5lptcNjWX9lcuOn3h3HgVFyad1BVsPPtLsyZPAaxtGYLt66X1jz/8y9mIMY1V7mRgIo7N+yyzF9RBFQFX7DsU1a3NKMu5MPpeBZbdh3BLbMuNvcaS69uQusVja69UMiv4Gs/eBWTxtTgbz82CbG0ey4/eiaBlu/8tmzzpmy9q/R8PJR2Dv/LGPs7xth4xli9+CuWiDGmMsbaAZwA8CLn/Hd9KTyRzS22Ow50QjM4dhzoxH1b9mHetPFYuXkf7prbhB0HOnOD3xHPGh7P6Lj3mb228L9/uh1nElnbsWUb29Gd1LDjQCdujE5w5blsUztmNtZjx4FOcLjLFHWLpXSs2LzXlVZRFFeaM4kslm2U57NsUzsuqAmW1AdnEln8/dPefbBsUzs0g2PetPG4b8s+V7zG0TWucmT9Zq1bIpv7xZ/U3OfJ2lcrNu9FLKXbwmXHrHkORxJZHUs37nH1/Y3RCVi52X1OrOeucXSNubHccaATd81tkqbxykt2fpdtaseN0Qnm53nTxnuGZQxe8Bxb6yv7XJPf9DvTX1ATtLVRxCl0/Tnbt3TjHiSyurR/RRhBENWNWGca6kLmmnnX3CbEUro5J3jNi2I+EuuXda12rr+yuXDetPGeecczOuZMHoMziawr3LpeWvPsSWnScsXn3vmrHacd+5SVm/eBc2DF5r2YN228ba8hynLGj6V03DW3yayDbG6d3FBX1nlzMObjoXTn+fb8/5WWYxzApEKJOOc6gChjbBSAZxlj0zjn+61xGGNLACwBgMbGRmk+NUEfXjnUZTv2yqEuNI2tNf8DwIiw3zMeAFxcH5GGX1wf8TzmlWdtyFdSmbIwWXu86ibaWGofFMpHfB4R9qMuJK93X+sGeJ8n0VfF+tpZj6FEKeO0VCIBVdpPpYwl0S8injgHpebldY5GhP2u8mRhpZxja32dnxnzviZkZRS6/mTHIwHV1j+ysOFOOccqQVSKvo5TMT9Y5wnneus1Lzrno2JrtXMuLBT34voIGIPn2uosD/BeW8Wc68xfFs+at8Cr/dY8vOZiMZeL7/2dN73Wu0rOx0PmzjPn/BLJX8GNsyP9GQAvAbheEvYo53w253x2Q0ODNH08reHyifYb3ZdPrEfHiZj5HwC6k1nPeABwpCshDT/SlfA85pVnLKUVLdOrPFl7vOKKNpbaB4XyEZ+7k1kzXbnqBnifJ9FXxfraWY+hRCnjtFQSGV3aT8XGr+gXaz97nUevvLzOUXcy6ypPFlbKObbW1/nZK704384yCl1/suOJjO7Zv4nM+XHnuZxjlSAqRV/HqZgfnPOgdZ3ymhed81Gxtdo5F3aciHnmfaQrge5ktuh6ac3TK66Yc535y+JZ8xYUqqNog9ccKuZy8b2/8+ZgzMdDZvPMGIswxh5gjD2a/z6FMfaZImka8necwRgLA7gWwJ/6Un7Er6KtNYo5k0bDpzDMmTQaD97SjG37j2F1SzPWb+/AnEmjoTC44lnDawIqHrp1ui38WwuiGBXx2461LYxiRNiHOZNG4/n2o64821qj2H24C3MmjQaDu0xRt9qQijUt011pDcNwpRkV8aNtoTyfttYoTsfTJfXBqIgf31rg3QdtrVH4FIZt+4/hwVuaXfEOd8Zd5cj6zVo38TJD2Oc+T9a+WtMyHbUh1RYuO2bNczgS8atYt3CGq++fbz+K1S3uc2I9d4c74zjZkzL7ef32Dmkar7xk57etNYrn24+an7ftP+YZFlBYwXNsra/sczydlaY/HU/b2ijiFLr+nO1bt3AGIn5V2r8ijCCI6kasMyd7UuaauX57B2pDqjkneM2LYj4S65d1rXauv7K5cNv+Y5551wRU7HjrFEZF/K5w63ppzbMu5JOWKz73zl9RXODYp6xuaQZjwJqW6di2/5htryHKcsavDalYv73DrINsbn3rZE9Z583BmI9Z7p27wYcx9jSAXQAWc86nMcYiAH7DOY8WSNMM4AkAKnI/BJ7hnP9zoXJmz57Nd+7cKQ0jtQ1S2xBDq9AYGggKjdNSIbWN80JtoyrG6sSv/PCc8jz075/uT5WIocmgjtVznVNJbeO8VdsoKdFQ2jzv5JzPZozt4ZzPyB/byzmfXs5yyrEpIYY9VbEhIQhUyVilzTOBKts8E+ctJY3TIWO2ASCTN73gAMAYm4ycjjNBEARBEARBDAmGktzA1wH8GMDFjLHvAbgSwB2DWiOCIAiCIAiCsDAkNs+MMYbci343A/gwcrfNl3HOTw1qxQiCIIghD5mFEAQxkAyJzTPnnDPGfsQ5/yCAc5sFCYIgCIIgCGKAGEo2z7sZY5cPdiUIgiAIgiAIwoshcec5z4cA/CVj7G0AceRMNzjnvHlwq0UQBEEQBEEQOYbS5nneYFeAIAiCIAiCIAox6JtnxpjwqdgzqBUhCIIgCIIgiCIM+uYZOa+CHDkzjUYAp/OfRwE4DOCSwasaQRAEQRAEQfQy6C8Mcs4v4ZxPAvBTAJ/lnI/hnI8G8BkAPxnc2hEEQRAEQRBEL4O+ebbwYc75j8QXzvkLAD4yiPUhCIIgCIIgCBtDwWxD8C5j7AEAT+W//yWAdwexPgRBEARBEARhYyjdeV4IoAHAs/m/sfljBEEQBEEQBDEkGDJ3njnnXQCWDXY9CIIgCIIgCMKLQd88M8b+Fzm1DSmc8/kDWB2CIAiCIAiC8GTQN88A1gx2BQiCIAiCIAiiFAZ988w5/8Vg14EgCIIgCIIgSmHQN8+MsWc457cyxl6FxHyDc95cIO3FADYAGJdP+yjnvK1ilSUIgiAIgiDOawZ984zelwQ/04e0GoB7Oee7GWN1AHYxxl7knP+hLxXRNANJTUfYpyKp6agJ+hBPa1AZQyigIpHWoDCGoF9BIpMLF8dCARXxtIawT4VhGEgbHDVBH1IZHTrnZl5hvwpD7w0XaZKajqDC4POryGZ1ZBzhmmEga9jz0fTcsUhANetjLS+T1W1pRDy/wuD39bbB2kbx2dpGWRtSWd1stwj3qodoQ0Y3zGPO8EhARTKju/rS2W5Z3cM+FYwBiazuGU92nny+oSQ203cMgyOR1REJyMeOz6eYY9vZF9YxIktrvQ7E+HSOK7/CEPDnxoHBOSKSMSXiyPINKAx+v+oaE6I8LavbrhcR31qGM461DGd9relFvZxtt9ZXfE5kdIRURZqvte2JtA5FAUL5NBG/CkVhgz1MCIIoAV03kNYMGBwIB6xriA6fAmiG5TpngMJgmwfca6VhSyfmFMCelzWOdT5xzl9BhdnmOrHu5tZQA2KqCQVy67RhONqR0RH2KUhmDUSCqlnPZH79FHOhdT1PpDX4FAaDAwYHIsHe/VBAVWzrtNf6IFtfUrrRW/8qmycHfffAOT+W//+27K9YWs757vznHgB/BDChL/XQNANdiQw6TvSgK5HBkg27MPX+F7Bkwy50JTJY/nQ77tywC4mshvfOps3wOy3hSzbsQkrTcSalYcmGXVj+dLsrr4xmmOHW/E/2pHAmpSGV0XDWGZ7MIKUZtmOxtIbutIbHXz6Io6dTrvKe3HEI3Y58jp5O4fGXD6I7reFMIitt4xJHG2Vt6Ipn8Ks3T6IrkcGTOw6hK5HxrIe1DWnd8Aw/ejqF77580FaPWCbXRmu87pSGmKR/ehzxUpqBEz3e56krkYGmGX0ZKkMKw+DojGdw5xM78cs3TrjHTr6d1v4WffHLN06YY8SZ9mRPynWOxPh0jqvulIZfvnECXYkM7vQYU90pDU/uOIR4OuvK92xKwx/fPSstT8vqruvlbL48s32SOF2JDIIKk14H1vTdKQ3vdMVd/Sbqa/385vFu6fUlxvOdZv/uRFc8P2c8sROd8QwMw/OdaIIghgi6bqAnraErkcF3Xz5gW0O++/IBdKc023V+Jpk112bvtTI3z3735YO980tag2ZwW14ijnU+cc5fj7980DXXiXU9t4YeQFcig0Q2N2d1xXPtEGvz1PtfMOek7758wMyzK56xrQPW9TzX9oNI5deROzfsNNeRM8ksYhnN7APZfOs1x3YlMjjRnbTVqZrmyUHfPAsYYzczxt5kjJ1ljHUzxnoYY93nkH4igBkAfteX8pOajmWb2jG5oQ7LNrVjx4EeDRrOAAAgAElEQVROaAbHjgOdWLl5H+6a24QdBzoRS+lYsXmvZ7hmcDP9XXObsHLzPltca7g4tmxTOxrqQli2qR06hzt8YzvOJLK2Y2cSWSzb2I5508bjvi37XOXdGJ3gyue+Lfswb9p4LNvYjp6UVlIbZW1YtqkdcyaPwcrN+3BjdAJWbt7nWQ9rG87m2yALF3Wz1kO00Vk2B0rqn+VPe5+nZZvakdT0vgyVIUUiq2Ppxj3YcaATMxvrpWNLjG1nX1jjO9OK8ejMSzo+N7VjZmO965w6+/vG6ATUBP3S9I2ja6TjLO1xvcxsrDfL8IqTNrj0OrCmX7apHRfUBKVxboxOsH22zg3WfGXj2dr2pRv3IJGt/rFGEMOdRFbHmUTWXNOsa8i8aeNd88S9z+w1155Ca+WyTbm12rpmWfcEIu68aeMLruOyOoi107qGxlK6dG12luXMU6wDzjTzpo03+0XWftEHXvOt1xzbUBcyv1fbPDkUzDYE3wTwWc75H881IWOsFsAWAPdwzl0bbsbYEgBLAKCxsVGaR03Qh1cOdaE2lPtv5ZVDXWgaWwsAuLg+UjB8RNhvhjeNrXXF9cpflC/+O8Mvro/Yjol6WMuwfrbWw1lPWX5ebZS14ZVDXWb+4r9XPWRt8AoXx4v19Yiwv+T+8Wqj6OuhRCnj1EkkoJrtLDa2nMet8Z1pvdKUkpf1uLW/xXk7l3wLlVdKWq/ySklvra+z7sWuc2fbIwEVw4m+jFWCGGjOdZzWBH2IBHyuNQ3o+7pmXSOdx51xrXMG4F7HS1k7RZ0Yg7QdzrKs4WIel7XdWi9Z+2X1FXGKzdHiezXNk0PmzjOA433cOPuR2zh/j3P+A1kczvmjnPPZnPPZDQ0N0nziaQ2XT6xHLJX7b+XyifXoOBEDABzpShQM705mzfCOEzFXXK/8RfnivzP8SFfCdkzUw1qG9bO1Hs56yvLzaqOsDZdPrDfzF/+96iFrg1e4OF6sr7uT2ZL7x6uNoq+HEqWMUyeJjG62s9jYch63xnem9UpTSl7W49b+7k5mzznfQuWVktbrOiglvRhn4rO1jcWuc2fbE5nquaNSCn0ZqwQx0JzrOI2nNenaCvR9XbOukc7jzrgdJ2IF1/FS1k5RJ9na7EzjzFPMcbK2e62pR7oSZh94zbeF5mjr92qaJwd985w317gZwE7G2NOMsYXiWP54obQMwH8B+CPnfG1/6hH2qWhrjeKtkz1oa41izqTR8CkMcyaNxuqWZqzf3oE5k0ajNqRiTct0z3Cfwsz067d3YHVLsy2uNVwca2uN4mRPCm2tUagM7vCFUYyK+G3HRkX8aFsYxbb9x/DgLc2u8p5vP+rK58FbmrFt/zG0LYyiLuQrqY2yNrS1RrHjrVP/P3vvH19Fdef/v87M3J9JKCQCX39RjPzYFg0XEtdlq9ZaW/zRja5sNPkWsbUL1Y9bYCnUWmw/2a22ZUFr2G8/WG21Ii0o1VX2q5TWVaq0rJpAAFkLRqD8LD8SIMn9PTPn88e9M5m5M3MzN7k3yU3ez8cjj9x75vyac95zzvueeZ/3wcq6Krzaegwr66oc62G8h0+k78HuulY3Yz20e8wsmwGu2ufxu5z7qak+hIBUPL9ynQh6RKxumIFZlRXYcbjDVrY02c5sC2P8zLSaPGbmZSuf9SHsONxh6dPM9n619RjC8aRt+sPtYVs58zk8LzsOd+hlOMXxCcz2OTCmb6oP4Ww4bhvn1dZjps/GscGYr508G+99dcMMBD3FL2sjmYnffi2nP6I4CXpEjA569DnNOIds+eCEZZx47M7p+tyTba5sqk/N1cY5y6gTaHG3fHAi6zxuVwdt7jTOoaV+0XZuziwrM09tHshMs+WDE3q72N2/1gZO463TGHu6K6Z/L7ZxknE+uAbajLFn0x85gMytlpxzfm+WtNcAeAfAHgDa7q/vcM5fd0pTU1PDm5ubba+Rtw3ytqGJltOFgSKbnGZC3jZGtLeNopDVXBXKQz+6Naf4xZ7/CGFQZdXtmEreNka8tw1XlRh05VmDMfYcgEWc83Pp72MAPJZNee4LuSglxIhl0J9gklPCJUUhq8Wu3JLynBeKQnkmRjyu5HTQzTYMVGmKMwBwzs8i5T2DIAiCIAiCIIYEQ0l5FtKrzQAAxlg5hpY3EIIgCIIgCGKEM5SU08cAbGeMbUx/rwPw6CDWhyAIgiAIgiBMDBnlmXO+ljHWDOCGdNAdfT1mmyAIgiAIgiAKwZBRngEgrSyTwkwQBEEQBEEMSYaSzTNBEARBEARBDGlIeSYIgiAIgiAIl5DyTBAEQRAEQRAuIeWZIAiCIAiCIFxCyjNBEARBEARBuISUZ4IgCIIgCIJwCSnPBEEQBEEQBOESUp4JgiAIgiAIwiWkPBMEQRAEQRCES0h5JgiCIAiCIAiXkPJMEARBEARBEC4h5ZkgCIIgCIIgXFLUyjNj7BnG2CnG2AeDXReCIAiCIAhi+CMNdgX6yS8A/H8A1uYjM1lWEZUVBDwiokkFJT4J4bgMn8AgeUSE4zJExuAVBUTl1PVYQoHKOYLpuAFJhKKqSKgcJT4JclJBPP05HJcR9IpIyiqShjCtPJEx+L0iEknFcj0hq6Zygl4RkURPGmOYV2DweEQkk4peD2M+Cud63BKfZCnPJzAIomBqA5Ex+DyCniaWUKBwnvV6Zn0z79sjMEhCT1va5aPF86bb3ycwCL2kyaxb0CsinlRNYQFJhCQV9W9HHVXliCSVVBtn9LkmC5G4DCEtK0aZzJRPo6wHJFFv58x4Wr5O6Y3hmf1hzDfzmpbeTiaz5ZtZD2MZmffllJdRXrU4kbgCQQD8ntTzEpAERGU19fwY2jRTToMeEaIoOPZTJKEg6BEhCKzXa8TwZ+K3X3Md99CPbi1gTUY2Rh0gc8416gXG8SJzHAh6RUQTCiSBmcawVLgKgUGfrzLHQqc8tXk+ElfgEWCe1yURspqaW43zujGdOW/zmKaNNYqiImKY8wOSiISiAgBUDgR91jHPJzDzuGtoI70cKZW/qnLEkoopP23c9IiGcTWH8W8wx82i1h44528D6MhHXrKsoiOSwLaPTqMjnMCCtS2YsnwzFqxtwbmYjA+Pn8eCtS2Q1VS8BWtbsOSFVnREEphviNsRTSAqq1iwtgUfHj+PczHZlNeprjhi6et6mnC63EgCb+8/hc6MNB3hBKJJxVTOsbMxPLvtIDoiCSx5odUUdj4mo70rhvM2+SRVFc9uO4hjZ2NYsLYFz28/ZCnvXEyGrJjrGEnK+Mv5uOm+TWmiSXR0O7eL3X3LKrfkYyxHC+uMyXh++yEsWNsCFXBVtvH6X87HEUlmtEUkAVlW8yE6g4qqcrSHE5j/XDPe3n/K0ufnYzLe3n8K89P3fLQjrMtkMqlY5PNcTEYiqehtdLorhq5owhLvfEyG7JDeGG7XH9pzZitH6fS2MumQr919dEQS8AnMlP5oRzhrXvMzymvvimH+2mZ0hFPP2PznmtEeTuCZdw5gyvLNeptqz59RTtvDCSiKattPU5Zv1vNSVZ71GkEQA4NRB+iOyzgXTepjwrPbDup6QeZ4kTkOHDsbwzPbDqIzLuPZbQdNc/Yz2w6gI5JAR3cCbae6HHWJzDy1z+98ZB3jO6IJxGTzvG4cB5/ffigjb+uYJssq2sPWcVoFT6dttq3XuVjPPRrbyFhOVywJRVHRFUsikpRN+S1Y24LOuIyuuJzz+DfY42ZRK8/5JCorWLShFbMuvwCLNrRi+4F2yCrH9gPtWLShFRMqSrD9QDtUDv36/ddPwrKNu81x17fiXCSJ7QfaMaGixJLXkhd26deN+c+6/AIs27gbMyeU25bfFZNNYQ++tBuzr7gQyzbuxv3XTzKFLdrQCr9Xss2Hc2D2FRfiwZdS9b4tdLFtvGT6sxbWHVOwdOMux/v+5ou7EE4ojtft7ltWuaVsYznG+twWuhjbD7QjaZOmt7KXbtyF7phiyTMqK4Mtdv0mklSwcP1ObD/Q7ig7MyeUY/uBdizbuBtjSnx6nIRNWxr7ftGGVowt80MQBNt4cYf0xnDbZyQt707Xcs3X6T7iKjd9H1Piy6mOfq+kt5v2jC3a0IrZV1yox8u8psnpog2tiCQV237S0i5cvxORpJL1GkEQA4NRBzgXSeKbL/bMQ9q86jRe2M7D681jhXHODicUXD62zHWe2mdb/SStcxjndWMet4Uuzpr3wvU79XvPHANVFVnTGsdDYxsZ456NJBFJKjgbSaI7pmTVmXIZ/wZ73Cx2sw1XMMYWAFgAABMmTLCNU+KT8P6hDowKePD+IfNi9vuHOlDiSzWV8fqkcaW2cS8tD5rydLpuDNPyLfW7T6OVP2lcqSXMqexRAQ/K/D330Nv9alxaHnR9371d17Ar21hOZr2B3tvUbdl29zjYuJHTTIJeUb9fJ9kp9Uv6Z2P7ObWl1i6Zn+3i9Rbu1B+ZctiffHu7D6f76q2OxviZz5gxnvGaJqeZ5Rv7yZg26BX1z07XhiJ9kVWCGGhykVOjDpA5NhnHCKfxwm4ethsrtPmIMeScpzGNMZ42vzmNtb3l7TSGOs0pduNhtrmXMSDodZ5L7Obn3sa/3sbUQjMiVp45509xzms45zVjx461jROOy7hqYjk6o0lcNbHcdO2qieUIx2UAMF1vO9VtG/dIR8SUp9N1Y5iWb3fMfRqt/LZT3ZYwp7I7o0lTvXu7X40jHRHX993bdQ27so3lZNYb6L1N3ZZtd4+DjRs5zSSSUPT7dZKd7pisfza2n1Nbau2ifc4Wr7dwp/7IlMP+5NvbfTjdV291NMbPfMaM8YzXNDnNLN/YT8a0kYSS9dpQpS+yShADTS5yatQBMuch4xjhNF7YzcN2Y4U2HxnHa7d5Os3XRzoiWcfa3vJ2GkOd5hS78TDb3BuOyzjSEXGc3+3m597Gv8EeN0eE8uyGgCSiqT6E7R+fQVN9CLMqKyAJDLMqK9BUH8Lh9jBmVVZAYNCvr9nahpV1Vea4DSGMDnowq7ICh9vDlrwev2u6ft2Y//aPz2BlXRV2HO6wLb/ML5nCVsypwpYPTmBlXRXWbG0zhTXVhxBLyLb5MAZs+eAEVsxJ1fvV1mO28Tzpz1pYqV/Eqrrpjvf92J3TUeIVHa/b3bckMEvZxnKM9Xm19RhmVVbAY5Omt7JX1U1HqV+05BmQhu7KnluCHhGrG2ZgVmWFo+zsONyBWZUVWFlXhbPhuB7Ha9OWxr5vqg/hdFcMqqraxvM5pDeG2z4jaXl3upZrvk734ROY6fvZcDynOsYSst5u2jPWVB/Clg9O6PEyr2ly2lQfQtAj2vaTlnZ1wwwEPWLWawRBDAxGHWB00IPH7uyZh7R51Wm8sJ2HG8xjhXHOLvGK+Ph0l+s8tc+2+kla5zDO68Y8Xm09ljXv1Q0z9HvPHAMFAVnTGsdDYxsZ444JehD0iBgT9KDUL2bVmXIZ/wZ73GScF++mFMbYegDXA7gAwEkA/5tz/vNsaWpqanhzc7PtNfK2Qd42NNHqu1Tmh2xymgl52xjR3jaKQlZz8SYB5O5RYiTlX8TeNgZVVt3IKXnbIG8bcCmnQ8voM0c45w35zE+SBJSlFaqy9MRX5vfo102f0/GCBrtG7boEAb50mNcrwZtxXfQK8GeElRkmWr9XslyXDNf1NP7sYT6vpNfDPh/BsTznNnC+796u29030NOWdvn01v5uyw76rG01XBAEhtL0Pdv1OQCUGj4bZdJOPo2ftXZ2iucm3K4/sj0/gLNMOuVrVw97GXFfRwC6vTgAvY1L089FqZNsOsiXsZ9KfZLrawRBDAxGHcB2zhWt45bdOFCqza0O4amw9PhkMxY6jS3aeGSZ12GcW63jnjlv65gGAKIoWOb8zAUmu3pZxl19fLSOccGMsc10b1q6HMa/wRw3yWyDIAiCIAiCIFxCyjNBEARBEARBuISUZ4IgCIIgCIJwCSnPBEEQBEEQBOESUp4JgiAIgiAIwiWkPBMEQRAEQRCES0h5JgiCIAiCIAiXkPJMEARBEARBEC4h5ZkgCIIgCIIgXELKM0EQBEEQBEG4hJRngiAIgiAIgnAJKc8EQRAEQRAE4RJSngmCIAiCIAjCJaQ8EwRBEARBEIRLSHkmCIIgCIIgCJeQ8kwQBEEQBEEQLiHlmSAIgiAIgiBcQsozQRAEQRAEQbhEGuwK9BfG2E0AmgCIAH7GOf9RX/OSZRVRWUGJT0I4LiMgiYjKCrwCg8cjIplUkFA5gl4RkURPPJExeCUB0WRPmJYmEpchMAafR3CdJpFUkFR5Tz08ImRFtYQlZBUq5/B7RNt8tHL83tRnrd7GsIBHhKqoiKfzziw76BURTSgQbPLxCAxem/oGvSJkWUXCWN90W2plW+5REpFQVCjcnE88aQ4TndpSFPS+s6tPZj4BSYQkFedvR1XliCQVvR+CHhGCwACYZVhOKnq/anKo9aFPYJA8oimO8bOxz7TvbtKIvZSRLV83ZWTmZZc2sww36Y3tY5Qfu7prcmPsh1hSgaoCQZ+5T7L1VV/6lyCIwiDLKlRVhcwBlaef5fS44BUFJBRVD9fm2aTa812bZ1TOETTNnyokAZBV61ytzaHGsSiWUPQ8InEFAgMkBtM45BEYGACFAwKDab7zCgyK4R6Mc3ZAEhGTVQQ8AqLp/0lZ1fPKrHskoZjme5Wn2kob4+3KCtjco6ya70dg0O/bIzB4pZ4xLnP8C0ipuvZlPNTyChh0hnyNqcWpPaRhjIkAfgLgZgCfBtDAGPt0X/KSZRUdkQQWrG3BlOWbsWBtCzoiCbSd6sL5mIz2rhjOx2Q8u+0gjp2NmeJ1xmR0x2VT2PmYjLf3n8L8tS2IJGX85XzcdD2aVNARTljSHO0IozNmziuWVCxh3XEZnTEZ73x02jaft/ef0u9hyQutWLC2BcfOxvDstoOmsISs4lw67+e3H7KUc+xsDM9kpNHy6YzJ+PD4eUuaaELB+YwwrS07Igm8vf+UJU1HNIG4rJrC/nI+jkjSHO9cNImObvP9quB639ndg10+HZEEZFnNnzAOEKrK0R5OYP5zzZiyfDPmP9eM9nACqspNMtzeFdP7dcryzZifIQvnYjLkpKLHSRg+T1m+WZcTU9tnpJEz0mTKW2b8bPke7Qjbpkn2Up4WP/NzRyQBn8Bcp9faxyibHx4/b3t/qUm2px+WvNCKjnAC89ea+0RRVMe+6kv/EgRRGGRZhaKqiKTHUP1ZXtuCrriMmKyYwhesbcH5uIx3PjrVMzZ0J3AumsR8y/x5AJ0xGR+d6rLM1Z0xGc9vP2QaB415zF/bjEhSxrkM/aIzJkPhgKyqpvnu2W0HEc24h8y5/6NTnWiPJPDO/lPojslQORCVVdu6P7vtIP5yPq7P97KqIpKU9TE+KqfK18p6dttB23t8ZttB/X46IgnEZFW/786YjEhChqpyy/j3zDsH+jweank9884Bk86WrzG1qJVnAH8NoI1zfoBzngCwAcBtfckoKitYtKEV2w+0Q1Y5th9ox6INrbh8bBkWbWiF3yth0YZWzL7iQjz40m5TvH9+oRXnIklL2pkTyrH9QDu6YwqWbtxlut4Vk23LG1Pis4TLKreEnYsk8c8vtGLW5RfY5qOVvWzjbtx//SRsP9COB1/ajdlXXGgKM+Z9W+hiS152abSwRRtaMaGixJJG5XBsy2Ubd2PmhHLr9fWtOB81t+HSjbvQHVNMYd98cRfCCXOYqiLrPdjls2hDK6KykldhHAgiSQUL1+803cvC9TsRSSomGdbk1RjP2IeLNrQibuj7ZIaMaf2b2WbGNHEbucxWRrZ8x5T4bNMkeilPi+/0OZf0mbJpJ9ua3Bj74f7rJ2HZxt22feLUV33pX4IgCkNUTr1VPhdJWp7lxRtaIavcEr5ofWr+1b6HEwq++aJ5njfOlZoukTme3Ba62DQOZubRHVOwaL01naxyy1w7+4oLbe/BUo903TlSK+LnIknHui/duEtPq3KgO6boY7ymh/Q2vs++4kLTHHEukjTdt5xeIc4c/+zyczseannZ6Wz5GFOL3WzjYgBHDN+PArg6MxJjbAGABQAwYcIE24xKfBLeP9RhCnv/UAdK/alw7fqkcaW28S4tD9qmBYBLy4OWNHZhxnKMjAp4HNPbXTOWrdXZ+NkYpt2fUzl2aYxhdvU15mnXlk7X7drQTZibe7DLp8Q3tMTfjZwGvaLt/QW9ov4ZcJZnYx8a42TGd5LzbGl6K6O3fHsrw6m8zLR2n92mN8qSm/hu28oYrvWVHb3171DBjawSxGDjVk61ZzrotX9mneaVUQGP/t1pTtfGB6d5T8vDacxwytc4x2sYx97e6mGse7ax3Ph/VMCDMr/zPTuNhVq9tO+XlgfBmLUN7O6nr+OhNpb2J49sFPvKsys4509xzms45zVjx461jROOy7hqYrkp7KqJ5eiOpcK1622num3jHemI2KYFgCMdEUsauzBjOUY6o0nH9HbXjGVrdTZ+NoZp9+dUjl0aY5hdfY152rWl03W7NnQT5uYe7PIJx2UMJdzIaSSh2N5fJKGY+sJJno19mC2+k5z3p4ze8u2tDKfyMtMaP+ea3ihL2eIb+8FNWxnDI4ksK89Z+nco4UZWCWKwcSun2ljhNC87zSud0aT+3SmtNj44zXtaHk5jhlO+3THZUq+2U92u69EZTaIzmkR3zPm+jXO/luZIR0Qf4zPTOY2FWnzt+5GOiOm+O6NJRBKKZfxzys/NeKjl1Z88slHsyvMxAJcavl+SDsuZgCSiqT6EWZUVkASGWZUVaKoP4ePTXWiqDyGWkNFUH8KWD05gxZwqU7wf3xXC6KDHknbH4Q7MqqxAqV/Eqrrpputlfsm2vLPhuCVcEpglbHTQgx/fFcL2j8/Y5qOVvbKuCmu2tmFWZQVWzKnClg9OmMKMeb/aesySl10aLaypPoTD7WFLGoHBsS1X1lVhx+EO6/WGED4RMLfhqrrpKPWLprDH7pyOEq85TBCQ9R7s8mmqDyEgDa3VPDcEPSJWN8ww3cvqhhkIekSTDGvyaoxn7MOm+hB8hr73ZMiY1r+ZbWZM47ORy2xlZMv3bDhum8bbS3lafKfPuaTPlE072dbkxtgPa7a2YWVdlW2fOPVVX/qXIIjCEJBEeAWG0UGP5Vl+oj4ESWCW8KaG1PyrfS/xinjsTvM8b5wrNV0iczx5tfWYaRzMzKPUL6KpwZpOEphlrt3ywQnbe7DUI113BkBK37dT3VfVTdfTCgwo9Yv6GK/pIb2N71s+OGGaI0YHPab7lgSGoEe0jH92+bkdD7W87HS2fIypjPPi3YjCGJMA7AfweaSU5vcB/L+c871OaWpqanhzc7PtNfK2Qd42NNHqn2T2n2xySt42yNuGgSEtqxoTv/1aTnke+tGtOcUfSfnnmvcQYlBltTc5JW8b5G0jjavMh5bRZ45wzmXG2D8B2IKUq7pnsinOvSFJAsrSE6Nm11NmULB8Xgm+9OcyvzkeAJSJ1rBS43WXafxeCX49TSpcEgXbsGz52H3W6mC6LgrwZim71CaNMR+7NKJXMLSVtS1t71GylhP02dQXDm2ZTm+Xt1M+xYggMJSmbfS0/xpGGfZ6Jb1fSx3kwhjH+Dmzz3JJky1+tnzdlOGmvMwy3KQvdXj+nOID5n4Ienv6wdgn2frKib6kIQgnCq34DxdS80/PXAiYxwW7+SlzjrObZ4zzJ9D7XB00PPOaXTMAx3EIgGW+M5WXMWeXpu+jNF0P0WtdRMpMU+Z3jmObzuYeM+/HKQ+78U+ra67joTEv/f7zNKYW/cjMOX8dwOuDXQ+CIAiCIAhi+FP0yjNBEARBEPmBVqoJoneKfcMgQRAEQRAEQQwYpDwTBEEQBEEQhEtIeSYIgiAIgiAIlxS1q7q+wBg7DeDPfUh6AYAzea7OYEL348wZzvlNecqrT/RDTnNhuMlALgyXey8WWS329i7m+g+Vug+qrLqQ06HSTplQvXKjv/VyJacjTnnuK4yxZs55zWDXI1/Q/RAjuc1G8r0PBsXe3sVc/2Ku+0AyVNuJ6pUbA1UvMtsgCIIgCIIgCJeQ8kwQBEEQBEEQLiHl2T1PDXYF8gzdDzGS22wk3/tgUOztXcz1L+a6DyRDtZ2oXrkxIPUim2eCIAiCIAiCcAmtPBMEQRAEQRCES0h5JgiCIAiCIAiXkPJMEARBEARBEC4h5ZkgCIIgCIIgXELKM0EQBEEQBEG4hJRngiAIgiAIgnAJKc8EQRAEQRAE4RJSngmCIAiCIAjCJaQ8EwRBEARBEIRLSHkmCIIgCIIgCJeQ8kwQBEEQBEEQLiHlmSAIgiAIgiBcQsozQRAEQRAEQbiElGeCIAiCIAiCcAkpzwRBEARBEAThkhGnPN90000cAP3RX7a/QYfklP5c/g06JKv05/JvUCE5pT+Xf64YccrzmTNnBrsKBNErJKdEsUCyShQDJKdEPhlxyjNBEARBEARB9BVSngmCIAiCIAjCJaQ8EwRBEARBEIRLSHkmCIIgCIIgCJeQ8kwQBEEQBEEQLiHlmRhUVJWjOy5D5en/qmtPMQQxZCA5tofahSCI4Yg02BUgRi6qytEeTmDh+p14/1AHrppYjtUNM1BR4oUgsMGuHkG4guTYHmoXgiCGK7TyTPRKoVaPIkkFC9fvxPYD7ZBVju0H2rFw/U5Ekkpe8ieGJsNtNZLk2B5qF4Ighiu08kxkpZCrR0GviPcPdZjC3j/UgaBX7Fe+xNBlOK5GkhzbQ+1CEMRwhVaeiawUcvUoklBw1cRyU9hVE8sRSdDK1HBlOK5GkhzbE47Ltu0SjsuDVCOCIIj8QMozkZVCrh4FPSJWN8zArMoKSALDrMoKrG6YgaCHVqaGK8NxNZLk2J6gV8SKOVWmdlkxp6qo+5ogCAIgsw2iF7RVte0H2vUwbVWt1Nc/8REEhooSL+7Dvc8AACAASURBVJ6+pwZBr4hIQkHQIxbt63uidwopT4MFybE90aSKV3YeRWPtNEwaV4q2U914ZedR3HttJUp9tG5DEETxUtARjDE2mjH2a8bYnxhjHzLGZjHGyhljv2OMfZT+PyYdlzHGVjPG2hhjuxljMw353JOO/xFj7B5DeDVjbE86zWrG2MierQpAPlfV7DaKCQJDqU+CwNL/R7jCMdzpizwVwwZDkmMrQY+Ihqs/icZNezH14c1o3LQXDVd/csSvyBspBtkmCMJKoZd6mgD8hnP+D4wxL4AggO8A+C/O+Y8YY98G8G0ADwK4GcDk9N/VANYAuJoxVg7gfwOoAcABtDDGNnHOz6bjzAfwLoDXAdwEYHOB72lEka9VteG4UYzInVzlieSmeKEV+eyQbBNE8VIw5Zkx9gkA1wH4CgBwzhMAEoyx2wBcn472HICtSCnPtwFYyznnAP47vWp9YTru7zjnHel8fwfgJsbYVgCjOOf/nQ5fC+B2kPKcd7RVNQB9frVu3CgGQN8o9vQ9NUX7up7oG7nIE8lNcZOPsWO4QrI9NJn47ddyin/oR7cWqCbEUKaQZhuXATgN4FnG2E7G2M8YYyUAxnPOT6Tj/AXA+PTniwEcMaQ/mg7LFn7UJpwYggzHjWJE4SG5IYYrJNsEUbwUUnmWAMwEsIZzPgNAGCkTDZ30KnPBjbwYYwsYY82MsebTp08Xurh+Mxzt4MidV+8Um5wOBH2Vm+H4DA0lhoqsFnM/05hYeIaKnBLDj0Iqz0cBHOWcv5v+/muklOmTaXMMpP+fSl8/BuBSQ/pL0mHZwi+xCbfAOX+Kc17DOa8ZO3Zsv26q0Gh2cPOfa8aU5Zsx/7lmtIcTRTUp2EHuvHqnmOR0oOjrBsPh+AwNJYaCrBZ7P9OYWHiGgpwSw5OCGVZxzv/CGDvCGJvKOd8H4PMA/if9dw+AH6X/v5pOsgnAPzHGNiC1YfA85/wEY2wLgB9oXjkAfBHAQ5zzDsZYJ2Psb5DaMDgPwL8X6n4GiuFqB0ebh4i+0Be5Ga7PEGGm2PuZxkSCKF4KPcJ8A8Av0542DgD4KlKr3S8yxr4G4M8A7kzHfR3ALQDaAETScZFWkr8P4P10vH/VNg8C+F8AfgEggNRGwaLfLDic7eBo8xDRF3KVm+H8DBE9DId+pjGRIIqTgj6tnPNWpFzMZfJ5m7gcwAMO+TwD4Bmb8GYAV/SzmkOK4XiIBEEMJPQMjQyonwmCGCzomKchBtnBEUT/oGdoZED9TBDEYEE/z4cYZAdHEP2DnqGRAfUzQRCDBa08D0HsjvotZpdMBJEv3D4HdFz20KDQ4xb1M0EQgwGtPBcBdIwrQdBzUGxQfxEEMVyhleciwOiSSVa57pIpkiRn+sTIgZ6D4oL6iyCI4Qopz0XAcHDJRBD9hZ6D4oL6iyCI4Qopz0UAHeNKEPQcFBvUXwRBDFdIeS4CyCWTM7SRcvjQW1/Sc1BcpPorlNFfIeovgiCKHtowWASQSyZ7aEPS8MFNX9JzUHx4RQE/vONKXFoexJGOCLwirdcQBFH8kPJcJNAxrlaMG5IA6BuSnr6nhtqoyHDbl/QcFA+RpIL71u0wnQA4q7KCnk+CIIoeWgYYBMjUID/QhqThQ1/6kp6joc1APJ8kAwRBDAakPA8w2uvp+c81Y8ryzZj/XDPawwka9PsAbUgaPuTal/QcDX0K/XySDBAEMViQ8jzAkO/T/EEbyIYPufYlPUdDn0I/nyQDBEEMFmR4NsCQqUH+yGUDmapyRJIKbTQbouS6GTDoFTF+lA9bFl+HSeNK0XaqG2u2ttFzNIQo9AbPgTILoXGDIIhMSHkeYLRXmcZNNNqrTNpE4w7ThJZMT2iMObYfeeUoDnLZDBhLKlg6eyqWbdyt9+nKuirEkgqCXnfPESlGhaeQGzwLPZbSuEEQhBNktjHAFIupwUBtxOmtnMzriqJa7BzPhOOQFRVdsaQpHy1tJEGvd4cbqgos27jb1KfLNu7W+1xRVFu5UjLk5Jl3DmDK8s145p0DtPGsAMhyT3t3xZKQZTVveQckAWvmzsTWpdfj4x/cgq1Lr8eauTMRkPIzrQ2EWQhteCSI4oSWOgeYYvBVO1ArLr2VY3e9qSGEDe8eNrk02/DuYdz11xOweEOrIZ8QvKKA+9btwLp/vJpMZYYZQZ/9K/uAV8Lcn72LpvoQNrx3GKvfbMPCGybhK5+5DEGviI5wAosMcrJiThVGBTy44a/G4+vPt9AKYx6RZRUdEXN7N9WHUB70QsqDgptUVCQUFQ+9vMc0PiQVFWIe/EkX2iyEVrYJonihledBQHuVqZkaDLWBcqA24vRWjt31RetbMaf6EmxZfB0+/sEt2LL4Ovz9zEuweENrRj6tOBtJYvuBdrSd6iavHEVGbyty4bhs26ddsVSfL9rQitlXXIhbrrwQt8+4BF9/vgXdcRmLMuTkwZd24/YZF+PBl3bTm4k8E5UVS3sv2tCKqJyfdk2qHIvWt1rGh2SeVm8L7S2ENjwSRPFCK8+EhXyuuJjsSuMKBAHwe9Ir7r2Uk3m9dvpFWDZ7Ki4cHcDh9gi++WIrTnbG8cv59ivLl4wJoPV7X8CogAc/vbsa0aSCC0p9ONIRweigJ2+vd4m+Y5SPWFKBqqZWlbvjMn7xh4NY/WabaUUOgB5/dX0I4YSin15X4hV1W9f3D3Vg0rhSPPC5SbpiPCrgsZWTUQEPVtVVQeXARaMDtPkwT5T4JNtNnSV5sn0u8Um2/Zmv/IMeEc9+pQZJlaPEJyEcl+ERGLxSfuSCNo8TRPFCyjNhIV8bcexeS66sq8KqLftQeUEJvnrNZdj3yM1oO9WNn7zVhk27jpvKMdajdvpFWPrFqfjWr3ebXrmv+u0+HG6PmOpbO/0iPHTzX0EQGM5FkmjctBcnO+NYWVelK9yP3TkdXklAkI4LHnCMCrOmJB84E7ZsAFwxpwptp8PYtOt46rTBeTVQVBVnI0mMK/NZ3tgIAkMsmbKpvWpiOdpOdWPSuFJdQemMJm3l+tjZKBiDSbZy3XxIWIklFHz3S59GV0wGAPgkAd/90qcRSygI5kHB1d4+ZPZnOC6jzO/pd/6qytEZk23MToS8vC2MJBT8e0MIsy6/AKMCHnRGk9j+8RnaPE4QRQA9ocOMfHgQCHpEPDl3Js5Gkvqq3pj0Sm13XHaddySpYP27f0Zj7TR95enllqNYNnsqFBVYsLbFpChNGluChqs/qW+e1DZXLly/07SCCEB/5a6tGP5y/tU43B7B7/efwuc/NR5LXtxlUbKXbdyNxtppmP3E2/jmi7vw9Lyavjc00SfsflA9UR/CBaVeHOmIYmyZz2RS0Vg7DZt2HU+tyPlEHD+XwEMv78HP76lBNKmY7V3rQwh4BWxdej1GBz1Y+8dDwBUX6grWKzuPoak+ZLF5FhjwUstRi5zee01lSt5dPEPkucOezD5aWVeFQJ42Rwe9IlbMqcKDL5l/cOVr5dZodgJANzt5al41yvLw1sovCqieWI771+0w2Wz76Qc9QQx56CkdRuTjxC1V5YjJir4RZ+rDm/HQy3sAAB0R+7yd7FMDHgG3z7gEjZv2YurDm9G4aS9un3EJPhHwWGxMH3xpN756zWWmzTLGzZWTx5daXnGOH+WDVxLwrV/vxpTlqXr+/YxLLF4YHnxpNx743CT9VT4AXRkjBhY7O8/FG1rRdiqMh17eg6VfnIra6RcBgKm/tBVFrW9VbvW2sciQT1JR8Y/XVWLSuBI0NYQwq7ICj7z2IY6di+CpedXY/+jNWDN3Jt7800mMH+W3lVO/R8j6DOmePVQVZ8JxOukuA7s+WrZxN/LVLNGEild2pn707HvkZjTWTsMrO48imsiPR49Cm4VEZcXWZjtfNuEEQRQOUp6HEf3dgKIp36c641iYMaifjSQtYQvX70QkoTgq7JGEYqskB7NMSnav4o0mHEYW3zjFUienCW/SuFL9VT6QNkOJy7k2MdFPnOw8J40rNf3QAXpML2ZVVugrilpaJ28bWj4L17dC5YAoCLigxIen76nBvkduwsVjgliwtgVTlm/G/et24Ia/Go9w3F5Ou+Oy4zNk/KHadipsUYJo45dzH+XrR6vAgDuqzT967qi+BPla8HfalBrO07hRaOWcIIjCQcrzMKK/G1A05fvS8qAlH7swbSJ0UtidJodIPPdd7Hb+sSdUWOvk5FnjSEcEK+uqsGZrG2ZVVuCxO6fTa/VBwMmDgfajRlOAZ1VW4In6EC4fW4JVdVXwiAyMMbyx5LOonX4RTnfGe81Hk3vtB1g0qVqU3Adf2o2ygL2canazds+Q8Yeq0a7amH6kb/wqtPLp94go80n44R1XYt8jN+OHd1yJMp8Ef57MQgKSiKb6kGnMaaoPIZCnDYOO42B8ZP/oIohigJTnPpAvx/b5dpDfX9dKmvJtp4Ae6Yg4DvSNtdP0V+1Aj+LgNDkIDPqr9J6DYkIQAEQS9u1hNOHY/+jNePqeGkRsJuctH5ywzXtcmQ9Bj4jH7gzhh3dciRKvCH+eJkHCPXY/glbMqcJP3moDkJKPaELBk3dX44X3DmPpxl3weQTEZRU8LQ7/ets0VJR6Lf2cmU84/Wx1xZJQFNXxx6WTnJreUmQ8Q8a88uEKcTgelhHwiPaHmORJudV+FFWUesEYUFHqzavrz4SiosQn4qd3p8x8fnp3NUp8IhJKfsxCBAasrKsyyfDKuqq8rZwTBFE46P1QjuTLsX1f87HbmAT0uO/66d3VFhdfvZ1eaMzzjSWfxdZ9pywbccYEPVjdEMLC9T2brVbWVeHhV/bgZGccK+ZUAYDJY4Y2OWQeoQwg9Sp9Xg2CPhGH2yN49LUPdY8Y//XhSXx2yjhMqAiiK5ZE0CNCFAXLUb+RhGzJv+HqCSjxSvi3f6jS3Y6tf/cw/vG6Sng9IhgDLkgr0rTyPPAIAkN50IOn5lWjxCehO5bytvH6nhOYVVmBVXXT8Z3/2IOZE0Zj3t9OhFcU0BFJWDadheMyXmo5ip/eXY1SvzWfpvoQnt3W8xw01YdQ6pMsXlmWfGEKAl4BTQ0hLMqQ7VVb9jmeAGr0BPOTt9osz0sup4YO18MyErKKWNJ8iMmP7wrBK6qQ8rApTvvBcTaSRNArob07ATXoQZnfk7d2OxtJWsav8qA3L3l7RQGl6ZVzbWN2qU+ClzYMEsSQh3Fe/CscuVBTU8Obm5v7nL47LmP+c80m90izKivw9D01ObkX6ks+dpPsk3NnIqGoJqW2qSGEihIvokm1VyXRyZ2cUYGNxBX9FbSmZB9uj+Dx3+3Hpl3H9bo31k5D46a9PT55GbDkhVbcf/0kk5/Xx+8KARwIJ2QsWNtiaYMn51bjvnU9njia6kMoL/EiJpvvR+XcMf8vP/1ufxSRQddY+iunQxWjvI0f5cPDX/oUumM9vprL/BL+c9dx3PBX4/HgS7vx9LwazF9r85zMq8EVjVswq7IipYh7JV02w3EZz247iMff+MiU5ql51YgmUh4Uxo/ymVzjaacQlvolqz9ym2co87kxpc/R20Y/x5QhK6tdsaTt8/3UvOq8uJKLJGR0hBNW5bbEmxcXg90x2VH2Sv39zz+1L0SGrHLdVZ0kMAS9Q+/grDwxqDfldkyd+O3Xcsr30I9u7WuViKGJKzmlleccyZdj+77kY7SzBKBv5Hvo5T1md0rrW10r83Z5LtuYUlo4ODjnEITUSptxo8+Nj/8esuHV8vuHOjB5fGnq2PH0ils4LuNkZxyzn3hbjzersgKRuIxoUkV5ide2DUr9ksU91Jq5M3H/uh0mRTiSUBzyV4b08ecjGaO8bVl8Hb7xq1bHH0/bD7T3uulM22AV1lzKMYYSn4TVb7ZZ0pT4JDy77SAaa6fh4tEBk2L0+BsfYfuBjtRzY1CMnJ4hoxmRSc4Yy9lH73A9LKPQG+JUtcebB2Aeu/JBoTc8RpIK5tv8uMh1IYYgiIGH3g/lSL6ObO1LPnaTrONGPpcTr90pfo210xD0iWjvTmDdf/8ZHeEE5q/t8abRHbPfCBSJ9zj3bw8n8Oy2g1gxx86mj2Hh+p2OtqKaranxfkYFPBYvBnb2s6sbZiCYPmluqB5/PpIxypvTRjvjBj4nWTvdGdc/f3SyGwvWtqA9nICiqI4b1SJxBavfbMPsJ95GIA8Kq2ZG1F85K/Qx0INFoTcMFly5dZSjPNV/mP5oGmlM/PZrrv+I4QMpzzniqLAZ7BvdbP5xk08mdpOs40a+hOKqHsY8a6dfhO/e+in4JEHfnFUbuhgvtxw1eSj4xR8OWnahr6yrgpCWJm118fE3PsKq3+7T/bCumTsztRs+PWn85K02rKqbbtnNvuWDE5b76YwmAVi9KGRuIix2O9HhjnFznuNGu7iie9WQBIbH7uyRkSU3TsaTd1dj7Cgfti69HqvrQ/jJW236G4pIUoFXYLYb1SQBvZfdi8JaiI19fRkLioGgV7Q836vqpudNOSy0ci4ws+zpXnpYfsYX7YTB1u99AQd+eAtav/cF/HtDqOh/NBHESIBsnvtAttPEctn8k+upZG5tnlc3zEB50IOOSLLXehjzXFVXBQ5YbAgZgM+seEtPIwkMf/r+Tfj4dNhiaywwBpVzTFm+2WTWIQkM+x+9GeDp15XPNWNsmQ/fvfVTCCd6bF4vKPUimlTMNtz1Iby+5wQa//N/Buq15qBr38PV5jmWkPUjjzPtjo0b9bTNoxeNDuh27ZePLUF7OIHFhhMCV9VNx4rf/Ambdh3XZSyWUHAumsQ3DadMPnbndIwOeBBOKLq9dWbZvdnGF3JjXz9OKByyshqJy4gkZZNNe6lfRNAj5eV4bllR0RFOWI/PLvHmZ0Nilj0V+VCgZVlFR8Sm/kEvpDycYDgEGZY2z7lA9tFFgbuBl5Tn/pE56YHDfpNJLwqf28mzN28bWpimoLqph5anY93Tm7OMYT+840pcv2qrKeypedVgjIFznnWjkKaEhOOyyV5bi7e6IQSPKGBUwINwXMa2j07jG+tbB9ILwZBVSIqd7piMZ7YdwOwrLsSkcaX4y/koBMYw/hN+nO6KIyGrupeULR+cwFevuUyXpS2Lr0Pjpr0WedGOXNdlEMxRjgHomwFjSQWqmnr972aTYL42C+eZISurhd4w2BVL4tltB3VZMspMPvIv9IbBQrfPEISUZ1KeiwFXclrwn7eMMZExtpMx9v+nv1/GGHuXMdbGGHuBMeZNh/vS39vS1yca8ngoHb6PMTbbEH5TOqyNMfbtQt9LJnbHYTva4WV5VZnLsdp2dpbGME1xzsWeTkufzYZwVmUFbg9dhK1Lr8cv51+N8hIvltw42eRjN+gVU23gFS22ztp1rbyKEq/tISfvH+pAeYkPoX/9Hb789LsQBYZrp4wjs4xhQtAn4sCZsP69O65gxW/+BM454kkV3/r1btMR2QGPqPvCdbKR1g5VaaoPIeARHeU44BUxf20zwvHUD8WgV0opQRyIJhV87RfZnz+yUc2NQm8Y1DaGzn7ibVz+ndcx+4m3sfrNtrzlX2g/zHTCIEEULwPxbmgRgA8N31cA+DHnfBKAswC+lg7/GoCz6fAfp+OBMfZpAPUApgG4CcD/SSvkIoCfALgZwKcBNKTjDhh2x2Efbne2Qc4lHzfH+2baXyqKml5NS036mt2osR7huIzumOHwCFXVbTez2RD+/J4aLL/1U3jo5T2Ysnwzvv58C+766wn40/dvQmPtNLyy8yiiCRXbD7TjSEcUr+w8qts6a9eNbaB5y3DaMKjZffol2vw3nIglFCydPdV0pPLS2VMRS6q2R2RHkwrORxLptxpA88M3ovHveh5z46EqUvqHpJMct53qtn223D5/w3VjX6Eo9Al6hbZ5BgNGBz2mQ1JGBz15Wz8tdP2H48E7BDFUcKU8M8ZKGGNC+vMUxlgtY6zX90qMsUsA3ArgZ+nvDMANAH6djvIcgNvTn29Lf0f6+ufT8W8DsIFzHuecHwTQBuCv039tnPMDnPMEgA3puP3G7aBjtxL1xBv7sdpywt0MBCTBMc++rGilVqvjptXq7riM7oSMrz/fginLN+Ohl/fgWzdNxe2hi/TNOnFZwfy1zVjyQivauxNgjKErmkwdRpJlxVjhHAszjjZevKEVH58Oo3HTXtxRfQnORxN6GzRcPcGkIN0+4xLL/dhtlGpqCGHSuBJaZR6mqBx4ucX8w+rllqPgHParxR4RY8v8WLA2JdP3r9uBW668EP9S+2l9tdkvCYgnFTzwq52Ysnwznt12MOvpg5nPVrbnzzgWCAy2z3axb+wrFAIDfnyXub1+fFcobyu3AcnhBMM8nRzqFQRE4oo+nn79+RZE4gq8Qn7WnDwCs8hpU0MInjw0UC5vMwmCyB2374feBnAtY2wMgN8CeB/AXQC+3Eu6JwB8C0BZ+nsFgHOcc+2n9VEAF6c/XwzgCABwzmXG2Pl0/IsB/LchT2OaIxnhV7u8H0dy2RRkPGVM42RnHCU+yeT/NSAJWTfv2eWjrWg52VJGEoquzALOPp81v6fHzkUBcHzjV7swtsyHJV+YajoRbWVdFTyioK8YazaEr+w8iq9ccxlKvfavGCePL8UP77gSPlHA91/7UG8DlcOSz73XVqLU1zPxOPrKFZgpHjF8CHgF3D7jEpPsrZhThYBXsH0GosnUoSaZfr+fmleNv6m8ABveO4yvfOYybHjvsEneWg51YM3cmRgV8OBwewSrfrtPP9An89nSVkgtz1/aH3nmBl3tZEzyIZ4dryjA7xFMJ+j5PULeTtCTVRUJxXyCYVNDCLKqQsrDS9Wo7Cx7ZXnY0Kfy1A8MY/sILBXeX+z89y9cv3Ow7fMJYtjgdgRgnPMIgDsA/B/OeR1SZhTOCRj7EoBTnPOWftax3zDGFjDGmhljzadPn3aMp6oc4YTs2oQi6BHxZMbKx5NzZ1pMDaKymjXPgCSYXL8tuXEyfnp3NYJeMWVaoajWsm3sOh19PvtEzH7ibfw/nwjg/UMdeOBzkyyvyJdt3A2Vc9T/tXXF+BfbDqIri2/n8hIv1r932HTEsgCY8mm4+pO2K3T58pU7HHArp8VMJKHYmmdEEortW49sdqE9Nq4i6jPedEy7aDRKfRIWb2iFwBhOd8UdV4sFwcm2lVme2/vW7QAYRry8upHVqKzg/nU7cP2qrbj8O6/j+lVbcf+6HYjK+THbSKocizLehi1a34pknlZXC37ICwe+8atWU/t841eteVGeyT4/xUgYU4nBwe0owBhjs5BaadZslHt7Cj8DoJYxdgsAP4BRAJoAjGaMSenV50sAHEvHPwbgUgBHGWMSgE8AaDeEaxjTOIWb4Jw/BeApILXj1i6OtuKceepd7fSL8MDnJiHoFdGtnWJmmDAzVz5WN4QQkxX4pZ54vQ1kUVnVV840d1xffz7jeOqgFzFFNXj14JbVMs3nc+YKmuYjWfNt67TxKphWYp+aV42gV0LbqW7Tit0T9SGTmzDtQBIAuPeaSjxww2S0nerGit/8CUBq5Xny+FJaoXOJGzkdauTqYi2bQqKd/md8W/HVay6zlenutF3oVRPL0RWTdSUKgK6Qr5k7E6/vOYGbrxifOsI7fRKhR2AAg/48+z0iVm3ZZyp71ZZ9ePyuECkgDriR1RKfhPGjfNiy+DqTq7d8bhgsZP6aTXKm7IXjcl68YRTykJe+vM0cjhTjmEoUB25XnhcDeAjAf3DO9zLGKgG8lS0B5/whzvklnPOJSG34e5Nz/uV0un9IR7sHwKvpz5vS35G+/iZP+dHbBKA+7Y3jMgCTAbyHlOnI5LT3Dm+6jE0u78eC9prLeHhC5qEhZ7ri+kpwd1wGGBCOKxhb5jOsKLfiVGfcZF/W20ajoFfUd41/fDqMxRsyVlM2tCIqp1zPLXmhFWe64gh4RctBJWV+yRLWVB/SP6/Z2oaVdVWOB6t8dLIbX3uuGSU+CVMf3ozZT7ytK86r32xDRYlXt1V9al61bnYipJWRuT97V0+zaddxNG7aqw/WpDgPP+zsKs+E46ZNqJlk20R2l81bDwC2Mu0VmH5ISpnfoytRH//gFmxZfB3Gj/JhVMCDfY/chOqJ5brN9IK1LTgTTmDJC626HWjMcMy75rXhZGfc+aRC2iDoilhCwcNfSo2fAOCTBDz8pU8hlqf2c9x8mqf8e/Ma1F8KuWFwuB68QxBDBVfKM+f895zzWgD/nv5+gHO+sI9lPghgCWOsDSmb5p+nw38OoCIdvgTAt9Nl7QXwIoD/AfAbAA9wzpX0yvU/AdiClDePF9Nx+4S2OvyTt9r0AfPBm6Yinl5ZnvpwagNeOKGgK+3vVduUt/SLU3WvFu8f6sCl5UGbY6QzNxqFenw0G5Rrp1XhEp+k2yqn6vMbbHjvMJ6eV6NvvPqX//wfvL7nBNbMnanvDj92LgJBYHj6nho8flfKf3KJz1ofbUNVNo8h2ubAjnACJV6zQkyD9cjDzkvFovWtaDsVdtyg5OT+K5qU8cJ7h3XPBo2107Dqt/sQ9ErY/EGPTK+ZOxObPzgBjyTioZf3IKFwnIvEHTx4KIgmVcur/WUbd+P+6yfp5lMq57ZKUoBkut8kZG4aPxNy/hb/VM6xbKO9+Vk+iCZUW69B0YTVjK4vFPIERjp9lSAKi6v3N2mTjZ8DKAUwgTE2HcDXOef/y016zvlWAFvTnw8g5SkjM04MQJ1D+kcBPGoT/jqA193UoTc0BVZbaW2snYZPBLwmJ/nbD7Tjmy/uwg/vuNLyirixdho27Tquu8TKfL3rFc0bZ4ybZjTleuH6Vn3l2870wmirDACPv/ERakMXmzYJbtp1HFv2nkRj7TQ0btqLpvoQfKIAURSgqly34xw/yocf3nElJlQE8dHJDPOMtMcQ0yl/DaGezX02r+azbf7LN24PiqGJorA4mSNNGlfquEHJJwko9UmmZyHg/XSz/gAAIABJREFUEfEv//k/2LTrOLYf6MBP767Glg9O4IHPTQJjwGenjMP3Xt2ry+esygr8TeUF2H6gHUs37sKTc6uxbKPZbCO1UbYaQQczkUnjSvXPQZ+EZ2xMRu69tnLAZHo4onKOXUfO6hs3O6NJbP/4DK6dPDYv+Tv1bT5OLwRSP/T+oeZSy0mV+er+SELBSy1HTHL3UsuR9CEvtGGaIIYybkeZJwDMRtosgnO+izF2XcFqNQhom//ORpK4ZEwgZQ/pYJN2aXlQ/974d5/G7TMuxqiAB63f+wIYgP/YeQxvLPksACCSkKGoHKV+D/7SGcc/v9CKTbuOY1ZlBX7+lRqoPKWEBL0SHr9zOsaW+dDUEMKijOOpt398Bl+cdqGjazw7Rbexdho2vHc45eVCFGwV3EhcsZzadrIzddKbNqhHEymltDcvGNrmPwAFs6vL5YhyWmkpLE52lW2nugHY2wdHZRVr/3gIs6+4EIwBHjHlbebHd4Ww/JZPocQnIuBNbQA0PgPa4RQnO+NYMacKq367Ty+jLOCsRDl50tDqqJmMNFz9SYs3nB7PL4WV6eGK3yNi1uUX4FwkiTK/B+ciScy6/AL487Ry7+wlRcnLCYBeSUDQK5p+6AW9Irx5Ojo76BUxp/pSLN3Yo5zna+W5kEfJEwThXnkG5/xIyu2yzrAy/OOcI66o2NR6THel1Vg7zXZwPtMdx5bF12HyuFJ0x2X84g8HsfrNNl3R/fuZF+O+53dg/Cgfls6eimUbzW65gNSqRjgumxS+FXOqsOTFXZg5YTR+enc1Sv0SOqNJtB4+i2kXjbbdEHiyMw6RMcvqTuXYMsx+4m1IAsM/fX6yHj9TGVBVjtUNM0yD7Io5VVjxm326kv/0PTVDZsC1c8Fk56KP3DIVHs1UJ1N2NMXWboOSZt//+Bsf4Q8Pfg4+j4DuWGooiSYViCJwNpLEt36922YluQZnuuMWt3NOG7sicQUPv7IHK+uqTM/gyroqrNqyr8cMwysi6BVphTnPJGQVkYRi2lD92J3T4RUFSHlwV6eZAGX2bb66LZZMeQuxHs9djdI81D8uqyj1i6axm7FUeNDbv/zJVR1BFBa3T9ERxtjfAuDpw1EyTw0seiJJBYvWt6KxdppuGqHZPxt90j45dybiiorGTXtNCkPb6TA27TqORRtasWbuTGw/0I4ti6/TbfIAs4mHTxIsfpq1a7OfeButR85h+a2f0pXrhTdMwr3XVFpWmVc3hCAKDPet2+FagTGSuRrdHUv9GNDczhkPeBkMc4zMcuxMBRxd9JFXhJzI1XOGIDCUBz0mTxbbPjqN1/ecwJIbJ+Mrn7nM4qXGuFrtlQTEkmZvNSvrqnDxmIDj8dpGt3Paj1WPwGyVqPPRBF5pPQ6VQzdRisQVCALw+F0hyz3SCnN+UTnHr5vNZgm/bj6Ce6+5LG9llPkli/KZLwptFgIOdMVki9yWB739zppc1RFEYXE7CtyHlJu5i5FyB/dbAA8UqlKDgeb2aPL4ng17RvtnzeUa5xyL1tkrvZt2Hcf7hzowKpByY+S0+W/y+FJwzrPaYp7sjKPEK5mU2me2HcCBM2FdETh5PgavmLIhzab89rbBKXM1+t5rK/FPn5/s6oCXfOH2NaOdqYCTi76R5papP/TlNa+qcotsNDWE8Kfv34SOiNndopaX5tN80YZWBDwSFq5vtqwwPzWv2tHU4idvtZls9Te8dxhfu7YSvow9BcZDezbtOo7X95zA/kdvNr3OJ9koLAGv6HAgTn4UOJ8kIBFXTWYho4Me3btHfym0WYjKYVlc0d6w9BdyVUcQhcWtt40znPMvc87Hc87Hcc7ncs7be09ZPGhulTqjSZOnCc3lWjguo9QnOfqp1ZReO7/KRq6aWI7D7ZGUonLDJMu1tlPdujsubXOVdiDDV6+5DI/dGUJcVrF4Qytm/ehN3LduB6Kyaop377WVfd5hnXloSW8HvOQLO88NduXYefUYE/TQscn9xG3795Zm0frW1KmAGR4utLyMPs0d/dzauAhbWVeFNVvbUqvOIkMkLuuHpAQ8oq4oMwZUlKYO7dF+/ALkYm4wyHYgTj6Ip12GGr15dMdlxG0OleoLTp5h8rVmUEg/z+T9iCAKi1tvG6ttgs8DaOacv2pzrSiJJVW83HLYYqqxsq4KYvp9oJN9pVHpZYDJr3KmzfOq3+7D6a44nry7GtsPdFg2+j01rxpBjwhRNB9lXeKTMGX5ZsgG91+Zr+LyvcFpoF7/uS3HyasHALJZ7Qd96WenNE4/MLW8NJvnPY1ftH2Wjp+L4ZWdR1N2/z4J3XEZ0aSCx+4M4UhHBKU+Cb9uOarH/+hUN053xRH0iuAqR4lXQsPVnzQ9W6Q4DDwFP6FPLdzKLQD9rZ7xjUapT8rb8eKFXNkeSO9HBDEScfuE+gH8FYCN6e9zABwEMJ0x9jnO+eJCVG4gMb5Cazsd1u30IgkZ333lAzx+VwjdcRkBSdRfO2cqvWvmzsQrO49hx+Fz+qvl011xPD2vGoGME/skgaHML9l6tHByUzQYr+LyWWY2m9pcynH6gUA2q32nL/3slMZxA1/6ZMx/bwhh1uUXQGQMj9053eQKTHuW7vnby5BUFHBIiMsK/B4RjAHlJV78oe00Hnntw9SP1XT8n99TA5VzsLRddXnQQ4rDIBNx3Mgpo3SIn9AHADFFRUc4jrFlfv2NxumuGCRRQGkeTEOCXtF2D0u+FibIUwxBFA63T1QVgM9wzhUAYIytAfAOgGsA7ClQ3QYU40CsnZAnCQz7H71ZP21swdoWNDWEcOxcxLRJpdQr4djZmGm1WmAMnHNc/YP/Quv3voC5P3vX1nfz7CfedvRokalsBiTB4t0gHytq2ZRaO48KfSmzN5vafJUz0sl1059GX9o/WxrN7aO2Yjcm6EHQIyIpK6j+ZDnuX7cDv5x/Nf7tP/aYNpT94LUP8fhdIdy3rsXi5aCxdhp+8lYblnxhCvY/erPprUM4odjLFmOkOAwSgs2Po5Sf5Pz8iCm0TXLQK+KLP37H9KZPmxPyQWrDrde04ZZ+5BFEceB2hBmD1AEp59PfSwCUc84Vxli8IDUbYJxWSU6ej+k7+jWbzsbaaQj96++wZfF1aNy0F42107DlgxOWQxbm/e1EAMCrrcesq9X1IbzaeszRFs1J2cz3ilpvSm2+Xv/15jqJXjP2n/74du1L+2czoUkoZi8aqxtCqXCVY1H6+PlwXNaPxdaYVVmBcFx2dC9nNM/QlOLuuExuuYYgIoOtn2QxXzbDBV65dXqDEo7LKMvDyrndhlvyxUwQxYHbmeXfALQyxrYCYACuA/ADxlgJgDcKVLcBRRCsqySrG0IIeEQoPKWUAObNgZoru1d2HrXsKm+qD+GVnccAAL/54CTuqrnUtMLgERjunjURc6ovtVVS3PjpzIdi4FjOvBogPflFkmlFqh+reG5sauk1Y//or2/XvrS/XZrutP9ycz1a8fS8GjAwjB/lAwCIArMeCNSQ+qHq9/R4z+gIpzzPPH5XSF+dM+4HILdcQxOOlN1weYlXN7mRBIZ8HdCd+vHmK9gPbu347EIcYgKQL2aCKGZ6fUJZ6mSU3yJ1DLZ2rPZ3OOfaVvZlBarbgOKXRJR4VTx+53SM/4Q/ZY7hk3D0bBQlXhErftPjNzkclzGrsgKv7zmBSWNL8JXPXIYSn2jxd6vZZa5umAGvJMKfHtSNqxZOg+Sgb9Tzifjy0+/mbUVkIO21+2q6UOwMFSXSqR4Br4i5P3sXK+uqoHLgxfeP4B+qLzGZQEkCgyQKCHol+CUJjAEBrwR/+seb8dnR+hkc5JZriKJyDpVzw2fkzWyj0MSTKnweZnaB6GGIJ1UEs5y06pah8rwSBJE7vc4snHPOGHudc34lgGHjWSOT1EY9D0RBgJq2cRMYw5igF8/90ew3ucThNDJto1+JV8K1U8aZ7DJzNnMYIGXTqZzD7ZG8rogU2qbZqDBnnvo4Ul6FDhXfrk71iCYUNNZOw8stR7HkC1Nw4+O/x/hRPnxm0lgAqZXoQHpV2XgCnV3djSYq40f5LGYeZC8/+HgkAfGYbApTVJ43P8+FPoJa4Rzf+FWrxfb+qXnV/c4bGDrPK0EQueP2Cd3BGLuKc/5+QWszyAgCAxhw98/f0we02ukXYckXpuiHhmiKsHY8q90glw/zg4HaQGdfTgiPvmY+QDLXFRG71d9C2DSrKkdMVmyPOtdOfRwpr0IHSmZ6W9lP1cNsi7qyrgoPv7IHJzvjWDGnCheP8WPfIzej7VQ3fvGHg7j32sqc7EgzX3mbThEcQW8bhjLRpIo/fnwGsy6/QA/748dncO2UcSjNw8ptoc0etIOztiy+Tt/LsmZrW95c7RkPDDKa+wXydMgLQRCFw+0ocDWALzPG/gwgjJTdM+ecVxWsZoNEpgJyuiueGiz5wNrhDtQGOrtyBJY64dBILisi2VaEsv2ocGtukbnKHE0qWLwh+6mPAc/AHDE+mBRSZrQ2D3gEtIcTJjtlu9U+b/rEP81dY0JW8didIdNm2ppH3uizgm/3yjsu5+dwDCI/BCRB96xSCOUw6BVtldt8mT3EkgqWzp5q2bgaSyoIevs/F0RlFcfORVL+zP0SumMyPj7dhaBP0hdnCIIYmrgdAWYXtBZDiKHk9WGgNtBllqOqvF8rmH1ZEXL7CtY+XkjfhKZh3Ni58IZJNgpfCBUlvmGpQOdbZoxt3lg7DY2b9tpvMAUgCKnDK+5btyPlM/3RmxFPqpYjmsv8Ut7MmmqnX4SlX5xqKmOkmOoMZYynSWrK7Yb3DuPeayvzohwWWrkt9CEsfknAxaODpmPsm+pD8NPKM0EMedwez/1nzvmfAUSR2kSt/Q1LMo+oHmkTsPEHRF+O+XazEUZVObrjMlSe+h9JuDse2v4Y6VYsvnGKKZ7x1MevfOYym+OiW+m4ZpcY23zSuFLHzYDz1zbjXCQJv0fQVwSjSecjmjOfr0yZ0PYe2GE8fviBz02ylFGII+SJ3Ah4BNRddSkaN+3F1Ic3o3HTXtRddSkCnvwoh0blVuv3ZRt3Q83TC4hCH8ISTSq620b9ePsNqePtCYIY2rgaxRhjtYyxj5A6VfD3AA4B2FzAehEFwq2CYvwBEfSk3NU5pbEowunDC4zoJ8yhZyVz/nPNmLJ8M+Y/1+w8UWW8gnVSzCdUBDGrsgKSwPRj0i8fW4If3nElSv0Ox0XnaRIc7hjbvO1Ut23ftp3qxtgyHxKyCsaA79zyKTRu2oug190RzXYy0R5OZJXP8qAHT82rxuTx9gp9b6/vc1HWidyJJBQseWGXSTlc8sKuvP1oLbRy6ziOxfNT/0IfX04QROFwuwTwfQB/A2A/5/wyAJ8H8N8FqxVREHJVUNyksbuuqCpWN4RMyqzR7MNu9fhweySrwq2hva7PjNfeHceauTOx/9GbsWbuTLT8uQOxpIq4rOoH4FjyztMkONwxtrnm29zYt0/Uh3D5BSVYfuun8NDLe9B2KqyvqDkp2+G42QuD/RsF59VjVeWIJhUoKu/1x5pT+lyfBSI3jBvuPv7BLdiy+DqMH+XLm3IYdniuM2WrrwgCsLLOLOsr66og5MmqotD1JwiicLgdBpKc83YAAmNM4Jy/BSA/hl9DnKG2OtWf+uSqoLhJY3f9vnU7UOKTHM0+7FaPn3hjv63CHZAE0/36xdQOdXO8EMCB+9ftwJTlm3H/uh2YdtFo+D0CGjfthaxyPHbn9IJNgsMFJ9kymki8vucEXtl5FE/Orcb+R2/Gk3dX44X3DuPjM2F906bRtMNO2TYeNKGV6dbnrRY/ISuIJBTcv24HHn5lj0XJ6c1Gvy/PApEbsUTKJtlotrF09lTE8rXy7BUtsrViTlXeNgz6PSJWbdmHxtpp2PfIzWisnYZVW/bBnyfvNQFJtIxlqQ2V9EaMIIY6bpcAzjHGSgG8DeCXjLFTSHndGNYU2o/oQNenL075e0vjdF071ALo2bhmd6hF7fSL8MDnJmHSuFJEEjJ+/pUa+D2pjZoBSUBHJGFyefbTu6stm5ACHhHz17ZYvG08Pa8GjbXTsPaPh3DvtZWmww7KfBL8NEnppGQrbjnquMSXOqCkxNtzCNDh9gi+++oHeOT2K3Df86l2f+CGyRbTju0H2rFpV+osJc3zxuH29EETsgq/xBBJyJBVDkDEG0s+i8d/t19Pk+nhxSj/T82r1le3gdxd1dEBFYVH4dx2w10+/STvPX7OdMjO9o/PYEzJWN3nfr/yjyu2x8dH4gpK/f1fPY8pWbxt0KZBghjSuH1Cb0Nqs+A/A/gNgI8B/F2hKjVUGGqrU/2tj5PJQ7bX272lcZunqnJ0xZI40xWH35NaPV5y42Qs/WLPytSCtS0IxxXdLWA0qerHPGv3W+KTsPrNNsx+4m1c/p3XMfuJtxFwsKsNeEU0btqL22dcgoBHwJgSr36dA+CcXtFrpDZsWjdVno8kMWX5ZnztuWacjybx/PZDkESG011xky250Twjc7X5dFccAmNYvKEV16/aim/8qhWqCtPq8ZTlm/HQy3vwrZum4vbQRbarx0b5z7QX3bTrOG58/PcA4GqTb1+eBSI3Cm3TG/CIuis87Y1T9SfLEcjTynChzTYCHgEVJX58/fkWTFm+GV9/vgUVJf68bagkCKJwuPW2EeacK5xzmXP+HOd8ddqMY1iTuTpVO/0iNNZO0/0LD7QJR39Xy4yv392+3nZKo5lTBL0ifnp3NZbcONlkRiEA/5e9b4+PorzXf9657D0BEiBykUIIUgWSlVAtFVtFLWJPUwoGkh4I6vFaPWjx9tPSNueI5SAxAv30g0K1ipwDilKac6pSqVpvVOWScCkC4SJXQ0iAZLO7szuX3x8z82ZmdyYEmBUC83w+/VQ2O7Pvzr7zzvf9fp/v85iuT1yUkNTa4AkhkGQFt48ZZK2SkJDUc3tZVJYMQ0lRX3oeKw7tgWZrvnT90YhJ3eFXq7di8JNv4bqqD3Dfso1uid4Au+arvG4+iLKCXlleiJKCaaMHQlGA+WVhRAUJvysPo/bXN2FIXgiLK4qx6dc34bkpYXh5Bi9MU6kdlSXDUPXXHTSjrDd1JWUlTW3g0ZWbMXvCCCyuKEZOgDebrxjmfyR+dnzRM7kXXJweMt1wl2m1Ch/P4m/bG0y9FH/b3uAYbSOasFeiceHCxfmNTqUACCETAcwF0BuqQYpukpKdwbGdc+iL//miJXu2dq5nomFtdYxKp0ia6CMLysK4f2wBDjTH8PRftqOhRcCC8jBygx7EkjIYAPGkjCdWbaHH/PddV9t2y//rks9MusCAml1cs/UIFpSHTZrNPQJ8mqPd3EmFqPrrDnrOoJejwZvxNRcqjHNdhx6M1j89Hk1tCTxkcEKbr+nRWplgLPvHPryztQHVU4rQGk+adKH180YTkm1m0u9hMfUPn6XdX3qD1bo9TRBEKc2Se15pIVjSuXvxfNJzv1DBEFj+Rk5d4kxntuMJCTdcnmea3/NKCxFPSAg45GDoqm24cNE10dm79BkAP1YUZfsp33kBQS/bPbpys0lLFkg3/uisO97ZwAn75TMx0Ug9JiKIWP7ZV2nmByXhfriu6gMAapY+KkjoGSI41iqgZ8iTxn/c3xTFjLEFGDe8Dz3Pmq1HsL8paukW2Ngq4GffHQCOYUz8ZQDICbQHQvuboqZM53cG5qDhZNz0nfTA8HQsoS9kGOe6MRD+48d7MW54H1MA3CvLi1hCApNFEE1IalbakPlbNHUkflPzT8x8rQ7zp4SxsCyMtoREf68eAR4BnjUFwzq+MzAHsYSEypJhWP7ZV6qhhjb39Aaxx9/cjJygFw+/Xmuag1VrdqB6Svg0vvM3Y0J0sYIl6nU13qshLwfWoWXRbv44dV/LioJVGw6a5tiqDQdxx5hBZ31uQB2/1frnrksuXJz/6OwTo+FiC5wBc7d1R1qyHTXyAXAsqE7NlsWTkmoIQKDSHDKcOTNaNP/rd7+F1rhaIvdy6r+7+dUFv6SoLx6/+dt4ZGWdbZa5pKgvsnwsyq4agAcNGc0FZWG8vfWI6XO/2NeMIXkhzJk4Ah6WxT2vbjA9MEfn56quX0TlMQe8LBpbBXAMoY1vPMtgdH6u6XPcEn07fByL7n6eNl9FBBGf7GpE9dpduH/sECo5NrhXEM1tCdNvZqwMfLGvGdl+Hlsrf4g2LbCOJiStKbAdcVGCn1fVBoznmldaiFmrt6ChRcDcSYUm/mcsKWP1JjWYiSVsmrm0Ksw3sZl10TESsoKln+7DuOF9AKj26Us/3YfbxwyC9xTHdgbGzZRxLjrV9On3sCi/agDaNBqFl2NQftUA+J06P2+9/jnF2XbvARcuMocOg2eNrgEA6wkhrwFYDUDQ/64oyqoMju2cwbjoPHTjZah+dyfuv77AljIBwNKO+sXbRqFNkBxV69CzZbKsOH7ujmDcICyZPgqxpEQpGDPGFmD6NYPAMAS1v74JWT4OB5pjpoxkU0RIo8C0xtVzGK/bgytqMWfiCAD/pJ+t8yR7Z3vh4+2NEXSqx4yxBbSDXX9oKIpC1SLatI0G64BF8IWEWFIyq22UhfHRY9eDEOA/fjIcr3yiZqHXbD1iysat3nQQ919fgJq6w/jOwBwcORGDAtX9LS/ba2mh3J3hQTgCjiEmFY9n3mmvGDz+pqrMoCsnBHgW5Vd/CzOWb0JetjctU65XYU7H6t0NLjIHvbm3eu0u+hrHEDxwwxBHzh9NSHQzZZyLt48Z5IjahpCUIUhmqtm80kIISRkB79mfP5aULO3Lbx8zCFlnuTadb0pRLlxcaDhV5llX1FAARAH80PA3BcAFFzxbLTrzSgvxt+0Ntg9rEFgGdLJsHVTrVI+zgVF54FTndiJIMH2e0m6LW1LUFxOu7I97X91gyv7U1B7CIz8cCkDNSPp5No0Cs+xOa86z7hZovM5+XuVZH20RLDcxRqpH9dpdWLenOeVaEPpAckui6Ygm29U2AJWaIUgyHnvDnNXr292HCVf2T8v29e3uozq7sgI89oY6P9Y89H1LubIlFaMwdNbb9P4KejncWP13U4Za538a56+fZ6mcYTwpYUnFKAS85nkdEcRT3htucJF5ZJpWwTPEMnPLO/T7yQpsaBv5jpw/4GEt7yUnMuen83xw4cLF6aPD7a2iKLcrinI7ABbALwz/nvmNjO4cwEoO7tGVmzFp5KXICXqwpCLd+CNV9qqkqC/WzvxBh5bTZ2u8cjqmEk44qRk/z/i9jFxwY8f4uOF98PibaqCsHsOlUWDs3OeigphmsBITZcxYvgnV7+5MM0ZYWB7G/LU7T3ktXNgjdT7df30BDXpTlQCsfu9YUqKqGn27++m5jIYpOvRKgfH+snNbiyckHGsT2ufv0vVUzjDg4RDyqRbyRnm6ztwb55sM5YUIniGWJiBOBbccyyDk5aiqywvTihHycuAcqij5PQwmXNnfZPIy4cr+8HucOX8m1TZcHXMXLjKLzq4ChYqinND/oSjKcQBXZmZI5xa2i46XtX9YG2SvJoT74rGbh+KJVVuwq8E6OIzExbMOZjurU+tUkGD8PKNMmF1wpL9e0DuE0fm5iMRFylHVr4uV+9yzk4soNcV4nfXfpabuMKr+2u76taRiFIJeDg0tgmkMrmbv6SFVVszudzVqOxtfD3o5VNZsQ03dYdOmyG6DdOh4zHR8wJMuHTevtBBNbQk8mKY/fQpXzE7cG25wkXnICuDlGZPUm5dn4JTCZ0KU0RxNmHSSm6MJJETZkfNnWkouk2obro65CxeZRWeDZ4YQ0kP/ByEkB51vNuxSsMuA2enH6iXl3JAHiyuKMXvCcJqxswoOF5SH8fIne886mO2sTm1HQYKe9TbaMkcTIiLxji2ak5KEBZqVtl1wpL+uKyds/KqZZqEWfVCPeaWFaGwVUP3uDsyZOIJaPQc9LLwskzYeAFg78wcoKeqLmrrDGDf/Q0z9w2cAUZvdXM3ejnEqW/dUQwg77eyWWNL2/nhhWjE+e/IGDO4VTPutUzdI89bsMB0fTUi0GXbn0+MxZ+IIPPOOOYut45SumJ24N9zgIvNgCNKkA1lCHJOqkw30MWMVw6ngPNNScqf7rDkduDrmLlxkFp1dBZ4FsI4QslL7dymApzMzpHMLKwUAuw5oK0tjo6qE3vikUxWiCVWpYuF79abzdCbjZcVb7oxObVSQLOWQDh2P4bE3NmNheRgelsG9yzYiL9uL3/x4GE7GkrjUE8CxVgE9AjyyfKpZRU6Ap81dr67bh0VTRyLLx6XpLs+dVIjVmw5iflkYL328hzYMVf74CqrmEBVELCwPIzfkxa6GCGa+VovqKWEoskI1pO2azRgCNLQIqhmL9nVdzd50GNVR9AyuHb/XqCxT0DuEllgy7XddUB5GyJv+e1eVFiHgYTH1D59jXmkhHllZh/yeQTyvldG/PhlD9eQi5HXzoeFkHH6PWQ1F53nSZlhFofznjhp1jdxN0/2RlJAT4DucD07IPrroGDzHIJmyGVG0152ALS3O68xvmGnOdsDmWePEHHR1zF24yCw6FTwrirKUELIewFjtpYmKovyzo2O6ImRZOa0OaKOlMdCuXWxccGvqDqOxVaCNGhGbBdnK6MQYEEQEES9/shcL36s3BT+n0qnlGFg21bCM3kRSi9//7Eoa1LbGRdTUHqKfM6+0EDzLwMezNKh95tZCvLO1Ab+p+SdKivriVz+6HM9PK0aWl0NLPImQl8O44X2w8atmlF01AOv2NOOLfc1Ys60BN16Rh8qabVSK7KEVtaipO0xlxoD2JsuOms2ORQRqxtLZa3ExwdgQV1kyzKTTTJuHNHm/AK8+XI3Sb7W/vgkrPttPN36RePv8M6qZ7GqI4M0NB/DTkf3p71NZMgy/f78ex9sSyPJxSEoKgh6G/tYzbxyibbx4S4UEoxmd/DXXAAAgAElEQVSQXr1JNScyBhgdNv8RYjkf3OAi80iKMmIJybKhj3WAN/xNNCRabSCd4mwTotLR9LW3JZYExxCQThr9uHDh4tyh01GGFixfcAGzDv0BnBv0dFpeySrzMX/tzjS3O+PD3i7jZbS7tnPxmzupEPWNbaipO0yl8GRFpWa0acfGkrIpCBBlUAtboF0ObknFKABAXrYXkqLg/mXWn/Poys14cfootCVE5AQ9mj05Q5Uz3tpyBAW9grjj2vy0LPzC8jDe2tIua3b4RAwEQPWUMA3G3tpyhDYS+VgGDEtO2Wzm97DUjAWA20VuASPXvaPrqDv5BT0sfvezMCJx1cwklpCw51gbxs3/EFsqf2jS1tbVTBZXFKOyZhuqSosw950v6XkH9wqm6Xw/ZzAvWfhePR4YOwSXaWobqQoD6j2i3kP6/EqVHjQGudGklGbak2qwoiM1Qx3gWdsA28XZwWi/DrSvPYsriuFz4PwsIXhuShi/eK3WNM866zLZGQT49ODWKUSTEl7STIiyfDwaWgSs2XrEct6eLlw1GRcuMouMPTEIIZcCWAogD2q1brGiKAs0vvRrAAYC2AdgsqIox4m63V4A4Baosni3KYqyUTvXdACztFPPVhTlFe31YgAvA/ADeAvAg4qinBHjTQ82KkuGWWeGBYlm6fTFx8rSuKFFQNDD2Wa0UukPbYIIP8eiKWouq78wrThNakh32qupO4y8bK/qUJVCl9h2+ASuKeiFkE89tx1vTy9tPnTjZWnZ87TPSYhpQfHftjeYgpVZf9qCqtIi+lo0IYJlCM1Q6xidn4vFFcX4pL4RFd8biAduGIKWWBLrdh/DNQW90HwiQa+pzptO/S0On4ilfx+30csEI9fd7jrWH43QLPSyO6/C8aiSpmkrKx1zP+dMHIG573xpcnNsS0h4ZGWdaU794rVaLKkoxv3XF2DN1iOICCJ2zB5vmXlWFAU8a3aRlBUFiqxYBhV+nkmT/FpYFgYURePNS3Tz6gYU3xwyzRn28gxYAaZ5whL1dScgK8CJWDKNNpYT8Dhyfj/PWJuwODB+V6rOhYvMIpMuESKAhxVFuQLAdwHcTwi5AsD/A/A3RVGGAPib9m8AGA9giPa/uwEsAmhz4m8AXA3gKgC/MTQvLgJwl+G4m890sHqwYdXkp7uepSpjpDZZ6e/t6DksywqaowncvVTtEL976Qa0JaQ0RQG7B09B7xDWPPR9zJ4wgga9xk7w7w3uRbvP7166wbYppTUmYnR+LgbkBmw/BzAH1+0NjrX4wWW9MW7+hxj85FsYN/9DNLQI2N2oZiqHznpbc14E/vuuq/HBI9dhQrgvbVrx8yyG9e2O+5ZtxGW/fBv3LduIYX27I+BhTVJ0Vs1m80oL4UnhTLqNXukwNsSlzumZNw7B81OL6VzKy1ZdAPWA19h8NfOmy9KUOID2DSVDCOUvz7xxiErfsVHkCHg5eDkGFd8biADPmuS/UmXk7lu2EddVfYDBT76F66o+wH3LNto21aaqIuga1Xdp95h+38ZFV57um0QmG+IAjTa3otY0T2asqHVsLch0Q6LRhGXorLfxxKotECQZQvLs1UJcNRkXLjKLjG1BFUU5AuCI9t+thJDtAPoB+AmA67S3vQLgAwCPa68v1TLH/yCEdCeE9NHe+66iKM0AQAh5F8DNhJAPAGQrivIP7fWlACYAePtMxqsHG6lNfqmuZ8bdu49jkaVl3/TMR3c/j1YhNVN7pUkTWg9GS4r64v7rC5DlNwcbJUV90RpP2vL5Kmu2YdmdV+Pm4XmmkuKfaw8h5ONM2QY/n25hO78sjJCPxeKKYkRteIP1RyMdBtepRiZzJxWi6q+qgsKMsQUWDWphBLVr1pYQabCjj/PxNzdj0dSRputf0DsEISnhmVsL0be7H/VHI6haswPVU8JpJipuo5cZRnqQkfoQ9LJoiiRw77J2U5tnJxfZbtYG5AYQT0h4dnIRHn69jjo4Tr9mEAJeFq1xgj9MHwUfz6jnfXUDllSMsq3ePLFqi7oBYhlT5lktVauboqCXo3bgemVj0Qf1aRlLnYIR9HKUZ11Td9ikUQ2ohi9tgojckMf0Pv07ugFFZuCx4Qx7HMryd3aenCky3ZBoDM4Bc0/H2cLYN6DDrrfGhQsXp49v5C4ihAyEqgv9GYA8LbAGgK+h0joANbA+YDjsoPZaR68ftHj9jGAMNhiiltAAQEjRDDU+bBmGIMvHazbPCnJDHgAkjQYxY/kmvDh9FCRFoQ/6dbuPYey38yhFwqiIEYmL+HR3Y1rQqwYdBIumjoSiKBg/vA/uW7bR1IxzImrWO97d2IY9ja00yI7ERXxS34h/X16L7wzMwaKpI02BkR5c52r85oaTcctFuDUu0qA2Ehfxyqft/OXbrhlk4sjq2eol00eBYYhtoJatNfnU1B2mTYRzJo4w8ZtH5+ciKkhuo9cpYEUPCvAsbeAy/jYPv16HF6YVp/3OM8YWICKICHk5hGSFzovmtoTJUfK5KWEQcLTRliFIc+OcV1qIk7EE1u1pwqoNKk0DUO+z6Vom2qgO8uQtl5sazeaVFiKekODlGBowtyVEfLyrfS7PnVQIwMyV163gU13cAFA7cTegyAxYlrHkDLMOmZjEE5KlGk88ISHgwO+ZcbWNDAbnfo6xVo1ySOkEcO3tXVzcyPgTgxASAvAmgIcURWkxdhIriqIQQhwqgnU4hruhUkEwYMAAy/ekBhv7m6KY+VotVYUAOnjYKmrndFMkgUtz0jO1Vrzh+WVhvPb5fqzb04R1u4+lKWLMnVSI975s5xW3xtXM8i0j+mDG8losmjrSshnnhYpiqoUMAHsaW1H8rRxTkD13UiFuGdEHNXWHcd+yjagqLaSZ9l0NETz9l+30+AnhvhYNkCqfVLdunjG2ALddMwgP3DCkY561tumwy4pEBNGUUV5QHoaXZdKzzJ72RfpCCno6M087C9kg+We8djlB3oaHypoC3hljC1B21QDcs9Rsu97QEscjKdkync+s8ze9PIvuAQ+qJxehd7YPB5qj8LIMnvrLdmrnfrfhvAvLw1AUlc40Y3mtpTqImpErVisaKQHBrB9djsr//SfdiB5tad/wGR0w9XPp72tsFdyqxRmiM3M1IcrWnGFCHHEBlBXFxj570FmfG1AbElMTC89OLnKsITGTwXlMlC1Vo+64Nh8hJ659F2lIdHJNdeHCiExynkEI4aEGzv+tKMoq7eUGjY4B7f+Paq8fAnCp4fD+2msdvd7f4vU0KIqyWFGUUYqijOrVq5flWPVgQ+ciP7FqC2beNBS9srzUZnrmjUPwwrRiKh0nSTKa2gTctXQ9PSZiwfOz4g0/tKIW44b3AQDccHkeDYSN/OXRg3tSDnGWj8cPLutNz5Pttw6CQl4Oj908lHKMvze4l+W5ddvsL/Y145Jufoyb/yGlhOiBM9DeAFlZMgw7nx6PxRXFyAl4kOXjqaGF3h3OEDUTfyoDio4E/BdXFNPPyU35HKMl+oWIzszTzsLWWdLmt4klZKrzvGP2eFR8b6DlvOnm99BS+e7f3kI50wEvZ+Jv3vXKerAMgdorDDylbcis7NxnLK/VxlvboTpIwMuljenBFbWYcGU/+p4heSF08/OUK293riF5Ic2dkgUILI1jXNijU2tqhjnDfg9rY5/tzGbI52HxzDtf0nuismQYnnnnS/gcOj9LiGVPhxPBecDDYuF79aa+lIXv1TtGUeoq9vZOrqkuXBiRseBZU894EcB2RVGqDX+qATBd++/pAP5seL2CqPgugJMavWMNgB8SQnpojYI/BLBG+1sLIeS72mdVGM512rBaDPQgU22gC6Ls6gG0Ge+uV9ajKZrA8s/2m4555ZO91F1NXxDteMND8tSGrX49rF3U9Ka97wzMwYHmqOk8dk5vLVqmZ/aEEagsGWbbvGU8t57xDXjYtGbJuZMK4eUZVNZsw66GCO5eugHN0SQApFlo6ziVu5VRY9cYFHMcoxqykHY6jJVVt4tTw65hKOjlLH9j3XhGf9hm+aw3Z34Pg0fGDTUFLI+MG4p4QkoLlB5cUYtYQkbAYIpiF8waqxV2rpVRQbKm+/j59vckJPg87YYvMbuNnCAhlpTwby+vNzUVugG0c8g0ZzjT9tlRQTTdE3pjdNShhkfjPNWD86o1OxwJzjtq8nUCbkOii4sdmax5XwNgGoAthJBa7bUnAfwXgNcJIf8G4CsAk7W/vQVVpq4eqlTd7QCgKEozIeQpAF9o7/tPvXkQwM/RLlX3Ns6wWRCwXwwKeocox/fBFC7zg1qJuXrtLtr8V9A7hFhCRFVpIS7ppja5tcaty3O7GiKorNlmyTc1Nu0tLA+DYxm0xtrPs3rTIUtO2+pNh6iGb2fPzRJV7imakLB6k7kMunrTQdx2zSDaENgZyaPOGFDoQTFwYVEvzhfYNgwJErw8Y2rCXL3pIO68Nt/EsTdSH4zHRwTJpsmp2DZQeunjPSb6kV2p2miMsrAsjLaERBtxewR4MASWx7bEkqYNmtHwpaSor6XJCsPAlfLKMOyakaOCiJADnOFMS+ExWmY43eHUOdqG0ZgIUHs6nKBtMAxMuu0HmqMI+VgwDqXL3IZEFxc7yBnKIndZjBo1Slm/fn3a65G4iLuWrjctBnrDGs8yuKSbD0NnvQ3RkJniGIIds8fjF6/VWjYlVf1VVen4089HY1DPEE5Ek3QhC3pYWsqeeeMQSxfA3JAH9UfbcOREFFf07YYVn+836dn+rjyMMUN6Iejl0BJLYvWmQ6j8339idH4ullSMggIFfo7F8ZiZ+7qgLIycoAcHj8fQI8Aj5OUQE2X4WAbN0XROqY9nMGt1O52DYwh2Pj3esYfIN4HTbG4551/Mbp52FlacxHmlhahaswP5PYOYfs0ghLycqhAT4OFhGfzhoz20aTWWEC35qn27+3HZL9Pvg51Pj8e/Lvks7f5ZUlGM8H++S99fUtQ3zUBlQXkY3bwcGtsSeHTlZuRle/HYzd82cU0XlofRw++xnJ85QQ/iYrs5UOp31zn5RpMVENh+j640r3Eez9WooM6hVM5wdz/vSENfa1yl2aXOucUVxY409MmKgpmv1eK+6wpMah7VU8KOzJF4QkRclE3Phe4BHj6Ogc9zdtdHkmV8fVIw3WdVpUW4pJsXrAMR9Blyns/pXO3smjrw//0lY2PY918/yti5XTiGTs1Td4uoQddsNgYLC8vDkBWV23L4RMy2yW3mTZd12JQ0JC8bLbGkyYCiqrSInmfhe/W4f2yBSfKOAFAUYNz8D7Hmoe9Trmd9Y5vJiCTAq9Jj+iJGM3B6c15SQk6wvRGy4WQcSUkGIQSCKOOVT/eZHK1yAh6TQoOHIbjt5fVdOsOgLvTp7oe5Qe8FSwNJzf7rkosAMOHK/ia1jGcnFyEU4kwbsx2zx2PW6q2mKkTVmh2YPWGE5X1w6HjMsrnqZCxpUpI5fCKGkI81zXUPy4DjGGT7eMwvCyPo4UwbWaNaS27Qk6YgwrKMqQkq9bvHkxLkFOlcN3OWefg8LMRI3PR7HW8T4PM44S+o2WdbVN+css9uE0Tk9wyaXsvvGXRMbYNjGSQE0fRcWFAedmT+GXXbAfUeemRlnbaxOPvg2bW3d3Gxw31KaPDxKv9s0dSRyPLxqD8awVP/t51KplWVFqaVf1UrWHTIaZ4zcQSgAA+/nr6Q6S5+3xmYg6MtAnpozlWCKKOm9hBKwmojlJEnqsu4GbNkVosYkO6mtuzOq5CUlLQMudHRiuMYZGlyRlk+HrKsWNqJn88KBUbJs2hCArGUD1QVIpwoH5+v0KkxsqLgxuq/Q5QVrHno+2kbvYdfr8OiqSNNlJ3WeNKypMwQpAUscycVYt4aNTCfM3EEBuQG0HAyDllRkJflS6uqzCstRPW7O2klY3R+LipLhmHN1iO4TdOPtuNTMoQgi22fn6f87rKCNkFKVx0J8Hh+6kgcN2T9egT483pedzWISQk+njMpqywoC0NMSvCcZWYVAEQZ1ooSY/IdGD3g51nLiqDfoTkSS0qWVMDFFcV0jp8pMk1pAVzqnYuLGxlV2+hKiAoqTzLLx2PorLcxbv6HJiOFS7r5sXrTQTw/rRg7Zo/HnIkjwBI16LZz0trVEMF1VR/YBgMFvUOUd5zl4/HKp3tpE1b51QPQPcBjdH6ufQOV1hhj1VRn1QDZGhdPu8HGrrnvfM0w6Fnmlz7agxPRJJoiiQ4aly68BV+WFVU5QlGogoRxfto17GX5eJNywdJP96U1vi4oC+PzvU3wcgwWTR2JnU+Px6KpI/Helw10U3dj9d+hKEBSUvDIys3YfawtTSHj0ZXtai/65xf0DmHClf1xz6sbsKuh4/l+OtdBNSVKVwUQJBmJFHe3hHT2zm4u2iHIiqU6iuBQU2bAa6Mo4VBDYiwpWY4/5pCiRCYD3Ey7O7pwcbHDDZ416LSNA81RGykvCSXhfvjV6q0mK9iEKINlCBaWmwONqtIi/P79es0t0HohiyUkVJYMw1P/tx1P/mkLSsL9DAGqF1leDosrilHQO4gFKec/VfbXqgHSTkHBuFhbBV/nUvHCajySJKM1noSsKGiNJyEZgp6opqddfvUAxJKqo51tMOZQ5/n5AllWr8exVgGKAhxrFdAaT8LPsTQQttuI1R+NoOqvOzBn4gjsfHo8xg3vg8bWOJUOfGFaMf55+CSG5GUhKas8TUUBYgkJtxZfSmXrZowtQP3RCLYdPoEXKooxJM86WNfVXvTPb40naeZ7cM+gZeDu5xjL+WB1HZraBNz1ynr4bRqBZRmWtvPnm9RWV4bRAdAoa+hU9jPTAWKms7dtgogZYwtM12fG2AJHxm+nnOSkGkZn7kUXLi5UXHiptzOEj2fxt+0NmDSyf5opyIKyMPwehpa+dRjNT/KyvaaSNccQjBzQHWO/nYdXPtlr6RYIAlTWbKOvcSxB3MS5bC9R9wx6KTWjTRBVikbSnmdmxenUNwZ2PM/zTfjeejxh8CxjdlYsV53vogmJbhr8PIcZy9dT9Qar63+eJs/PGHFRQmsKh3JeaSF4lsGGr5o1ShKXbpmsNd3NvOkyBD2q09/v36/HYzcPNZXc504qRG7Qg2NtibTPmLV6BxpaBCwoDyMn4EGPII97lm5AZckwyzl3oDkKjiH0vCEPh0nFl1I6k9EVsyWWxLrdx3DtkN6IJc1mQ/pvH0vIYBitEqTdk2q1xVrdoyNqiAtnEE9ImPUvlyMSVzckXo7BrH+53DEHQD/PWtp/O0WryLTDoIchlrQQJ+zLYwnZUjnpjjH5CDnAeT7fnhUuXHzTcNU2NBg7w/OyvXjoxsswIDeA/U1RVL+7E/dfX2ByPQOADx65Dk+s2pLW7a07pC2aOhL3LduIdXuaTFJ2rfEkKmu2oXpKGPuboqZO6ywvZ2tfezoLltV7n586EglJTmucC3o5+Dg1GL/rlXTFkW9avkvnLEOBrQJKqmX3M7cW4rE3NlPnxgduGGJSU9Cv/5C8EPY3qdc65OXsnM7O+ep/JmobdooxSypGIZaUTOoT0783CFl+Dq1xEa98shcL36unPP5sH4eEJNO5azzX4opiS4WDypJhGDf/Q4zOz02b96lKNGqzrIJLuvnRJoiIaSoof/x4r9ZYGMSh4/E0bn6/Hj5M/cPnaZ+t//bPTi7CM+98iWcnh6kyTv3T43H4RPq5coI87rL4Hl1Qqu68natRQURzNJHuMBjwOBI8RwURgijjZKydt97Nz8PLMY6cP5NqGAAQiSet56ADvRjRhIjmNotrH/Qg4MTYBfFMnhWu2oarttEV0Kl56tI2NEiKQpv6VtcexnVVH0BRgBur/46ausM0e9kZ8xOdV2p0AaypO2xyC9TF9nNDHhAC5IY8HQbOwOm5OllxlbN8PHKDXiypUF+bM3EEnv7Ldvzby6pBxLkWvpdlBdGESKkHAS+LypJhKCnqaxrPpTmBtDH26+Gnzo3TvzcojSpTU3cYlTXbEBVEdA/wWLf7GOLJC4vj2pEphZ9n8eJtoygl41d/3oqoIOLeVzegeu0uOp9+8VotWrXM2qnMTIyv6zQMq3lf9dcd1KFy0dSReHPDAVwz9331s+IiHlpRi4DBLa41LtKsmW4esXrTQUQ1mlPqfNB/+4dfr8PDPxxqoqZEBOtzMRbubgvLw2lUKLc0febItMOgpCh4dd0+CKJ6HwuijFfX7YPkUEJIVgApZbCSrDg2/oDNveRE4K9XUo29CX/b3gCfQ1n5c/2scOHiXKNLpVgyCSM/Ty9zfX2yXZ5Obx7UqRnRhGRrAtAaT1Luml3JWpWTa+cPd6YMeLoLlm03NEGaJu+M5ZuwuMLaUKVNEBH0nD3X2UprWZYVxERJlbJKqFy/VOrB3EmFAECVSQ40R03nNfKXv9jXjJCPw4moYFnSfXPjQbyzteGCpG3ormJWMnKPvbEZC8uvBABaQZlfFk6b84s+qEevLC/lievnKinqi5k3XWY75+uPRuh/6+6X+ntq6g6jsVXAkopRYAhBxfcGYt2eZtx/fQGV0zK6xYW8Ztm8dlUYFmu2HsFTPxmO56aEUX80gjVbj5h++349/HhoRS01Wcnymc+lZ919HhYkClRPLkJeNx/2N6mSeYBZraWpLWGaQ8ZKz2lqh190yLTDYMDDovyqAWhLtNNCyq8a4GgAJ4iyaS16dnKRY7QQu/s1KkgI+c7u0RxPSrjh8jwTvW1eaSHiScmRzHM0IZkkKOm96Eo9urhI4GaeNcQTUprtMCEEi6aOpNmpxlZBbRZRQBvnUrNXcycVYumn+1B21QD4OSub6jB6Z3tPmxuWqpqg43RVCICOg/DU8c6dVIg/frz3rK2LdRrJXa8Y7ZAFRBIi7l6qWp7/8eO9ANKzVbpN+uj8XFUH1ceaxjivtBAnYwl6PeqPRvDA/9QiW2u43Pn0eDw/tRg8y2Da6IGYM3GE1gB5xl/nvISfZ9IaSxeUhfG37Q20SiHLwPNTR+KDR66znPO61bbu8vfBI9dh929vwVMThqOm9hBOxpJpc35eaSEWfVBP58vqTYfSqjQqL3oL7nl1AwDghWlqM6GeSTZmtCOCtSpMW0JSNaqXbaDjLbt6APweBp89cQNqf30TAOCpCcPBsQyeWLUF9UfbaOb5y6duxpSrBuDeZep8e2TlZiQlBbKs4LqqD3Dvso2IixKdp/VH26iUWGqlx3o+u/beRkTt1iuHGvqEpAyS8gQjjPq6E5AN1Uj993/49TrIDmW2OQbp92t5GJwDT2VZtsn6O1Rs83MMyq4aYFo71GeeG1K4uDjgbhE1SIqCVRvMDRZvrD+A264ZZMo2G7NLVtrQuqvguj3NVNbtbIXk9Qf18s++srQtPl1tWjuDiFhSpiYUAQ9n+X06yipYZeIAUP5yuh1yLeZMHEG5sROu7I+Ax7qUqQdajS1x9OsRMJls+HgGs/9vuyF4O4gFZWEIoox7UxoLFUVB9wAPQuBY+fV8QUyUseKzdN3bccP7AFCvo9/DoLlNzew/P63Y0mr7+WnFAABJAc26GXnSR07EqL334RMxEADVU8KIxEW8rPGnW2JJvDCtGCGfyqsWJQnPTg7j65MxxJMyfvFaLT3vUxOGAwDWzvwBqt/diWwbykiWj8O9r24wjffB5bW0x0AN0LeioUXAvNJC9Mry4vfv11POtf6+VDOjRVNH0s+QZWD5Z1+hsmQYnXO/f7/eJFupz2/X3rtjMIRYGuc46eAYT8ppzasBh6TbM0mrANT1hyEwrWWMQ+tSprP+MVGmMn4AqIzfkumjTIZFLlxcqHBXeQ065zK1VBz0sBDE9myzEdGEWRvaqMRhNHU4WyH5aFLC8s++wqTi/gCB6WGxsDx8+t+VZ22NTxiGIOjl0qyLO6KHSJIMQZSpykGqEsKxVgGX5ljzw3X+8v3XF9AAx5IKExNpQ9rLt40CE2zniouyQoO3oJfF7WMGgSUEXo6hAVybIIIhACEEJ6JJdA+ojUUXEgIeVfe2eu0u+hrHENw/dgiA9iqFrkSRZRMcZHk5PDH+2/jFa7Wmjc29y8zKG794rZaaCC2pGAUPS3D7mEF44IYh2vVWgyRFUcCxDB5+vRaP32xxXoPb4bzSQkQT9ioHHW2sVm04iPuuK8C4+R/i0ZWb6ab265NqsN+vh990vN5Emu3n8dFj18PDMQh4WUz/3iC88ule/GhhvRrcp9JEDKouqWNJvUcudmpH0MuaVFOcdD43cqqB9s3fkopRjpw/qknJpVETBNERcyVZAf79f2pN81y/l84WUcGGVuEAJQRwOc8uXFxY0cNZwMi5NBmIJCVbikWAZ/H81JFUDsuIM6FT2MHPM5hwZX8kJcURbdpTGZ/omenOfB9JktEUTeBoq5A2tgeX16L+aBueWLUFERuta52/rDdZWjVmzp1UiKCXpeV/SQGOnIzjoRW1GFH5V/x82UZE4iLueXUDmiIJcAzBHz7ag6G/egf3vLoBR07E8ceP96ItIUFRlE41Z3ZF2P1u9Ucj9NoZ6RF2+uNtCRF53Xz0ffrGxo5KM6+0EIIo4lhbglJw7l66AW1ag52uCf2rf7kced18lGf925+OSDvvoys3A4C1zjPPWuri7mqIoLJmGyZc2R+De6l2yrrxy9BZKj2DELMucElRXzx+87dRWbMNl/3ybTz2xmZIsoKZr9Xi3mUbMOHK/pj1o8vTaSJaabozGsMXO7XDyzOIxCXct2wjLvvl27hv2UZE4hK8vDP3Xaazq5wmJZdKTeAc2vwEvKylDrYT4+cZWI7doUvvmrC4uOjhZp41dCSI31GZMSHJWP7Z/jQdYSctrPXAftmdVzu22+/IWtUuM+3nGER0jWktsygrCh5cXms7toLeIazb04RXPt2L+WVhPGTQNK0qLYKHJSbzDr08brSJXvrpPtwxJp9ylROSTPWx9cAqwKH3QHYAACAASURBVLNYXFEMP8ciIcmmDGjAo2aj/RwLlmGQ5YDO6fkIq99tfpma/a8sGYaqNTswe8IImtUN+di0easbKRibmVJdCY2yf4umjgQB0BIX8dgb7VnAXlleRBMSemap944oywjwnEn7tyPnx5c+3ptGP7nz2nxLXdy3thyhAf0LGuVEb9zdMXs86o9GsGrDQdx5bT61Fn903FDarAi025Q/c2shrn3mfUrnMMr1GUvTugmF1bXTYVTH0Y+/mKgd0YSENzccMP2Ob244gNvHDHLkHrRrXnUqMyzKoProqXrjTkDvOUiVk3NCBzthcHcE2ufu4opieB0Ye2fmv4t0nK4Mnittd/7iwl/BO4kz6XxWH47qAlXf2EYfEtGEM+oUOvTAXg8w7UxOnIIxMx3wsEgkJSRlBYQhONYqYP7anZRX2kfLUNqNrTWeBAAsfK8eP7++gPLHdzVEMPedLwGogfLgXkGqjvHWliNobBUof1lvCuse4MGxBAwIpWNE4iI4hqAtIeLeZRtV3WoPp5bHCaEqJhdqwGxE6u+2vymKp/+ynW5IRufngmFAA+yOjBQUKDTQrD8aMZWAI3GR0hr0TVAfQ6baStt5QVkYXp6h1YsnVm2xpehEBcmSfnLHmHzLgKCyZBiAdqUVfUO19NN9WPhevUlh42QsSa+PVeDer4cfax76PhZ9UG+S3DO+R6dg2F07EBkBnr3oS9t2VDinvj/HqA3dqTrMTmWGfTyD4m/lmA2ZysLwOZS+teqzWbXhIG4fM+isz51pd8RYQsa2wyfSNhY5wd6OmLC4cHG+w53lGhgCSxWBjtZh48PRqOMcdNjCWi/HW1EazjTDfSr9Wj0zrcgKWoR2RYwnVm3BzJuGoleWF4+u3Nzh2OZOKqRB/XcG5uDg8RgYQqAoCiprtqGm7jC9btNe/BwhD4eF5WHsmK3qkvbr4VMzxjwLQOUqi5KCvccitONdbfxTEPKpyhq6AcOFRsnoLPTfTZYUBDwsGlsFcAzBzBuH4IVpxfDxLPw8gxenjwJDgInF/U2l3YnF/emcX/H5fmqXbSwB67SGW0b0wbo9TXhkZR0ihjJuKs1Dz0ITQtAUUVVR9GY+qznDEFiWhO0y1brGtF42XlxRjA1fNaN67S7cMqIPpV5c9su3MfP1OpyIJuhmOfUzooJEVUfsaC06d7n8anNZ/NZRl2LW6i146aM9iGjl67Uzf2DSpXaSznW+w5YK59D3l5X2hsGhs9S1KZ6UHWsEjiUlulmjVLQVtYg5ZOFu1DbX55DaNH32m4uO5rcT4BjQjYVOySn+Vo4jSiEuXHQFuFNdg5djEPJymDNxBHbMHk8pAh01lZ0ON/hsoJfjG1sFVL+7A3MmjlC5yhWjOiV5lxooS5J8Si6mfkwsKafJdel8Vz2TMa+0MG1sz9yqZo13N7ZRiT6eJVi96SCORRJpG5UFZWFIigwvz9Kmor9u+5qOR28OZAjw7T7dcCKaRGssCZYQBDycRsfgL9qgORUxUaLB75dP3YyyqwbgnlfVAPKupRtwIpYEQ4AsH2cyUsjSqixBL4eF79Vj3PwPcaQlnhZE6HMA0IxRfDyenVyE0fm5JpqHnoV+YtUWuvmKJ2U8fvPQNAOVF6YVY/WmgwCsN7J2PEud061rQd+9dAMK+/eg9BIrXrXdZvlkLIFeWV6IkoKQl7WUEtPluDwsY1oveIYgfGl3TLiyP73WT6zagsduHooJ4b5ntdntish09lNWFNp8ajT5cUpKLtPjz+Tm4kySQacDUYblxkK8sHynXLiwhUvb0MCyjNpExhAaqAV4tsNgrCPVCieRWo6PJlTpt850TatNS0KaJffyz/ZbcjF9LENNSzpSySjoHaIGHD6OMZlNzHytFg0tAhaUhZEb8lAnw4YWgSpwCEkZiyuKVXMUQYSfY7H7WBvWbD2Cn47sj8fe2IwFZWF8vKsRI7+Vg1+t3or8nkHcds0g+vv4ORacm+qwhB78Vq/dhY8euz6Nj5wQZfAcgxZBTDOSCQVVOszvysMYPbinLX3BlPFNiMjWAvGYQQrRGLwC7YoIiyuKsfu3t1AVgL7dB+GT+kZUfG8gAMDPs1TC61hEgJ9nEfRyeH5asclO3MjpXr3pIMYNb8+G63J6VmP3cAx8PGOSCfOyDP6y5YiJcjJjbAGen1aMkJfDgeYoWEIgiDJ8HhbHo0lUv7vTRIux4klTBQiCi0ptw84kqk1zsDxbBCyMrRZ9UO+YlFymx5/J4JwhoMkgfX47qW2f6WZNFy7Od7jBswEsyyBLC5Y7szhaBbWZejh21ODXEaKafFyqvvL8srCJU6pzMY+1CqaGrOenWrsOHmiOYl5pIarW7EB+zyCmXzOIaihXTwnjRDQJnxbY5gQ9qJ4SRpsgalkVgqOtArppXLn7UrSYda1pP89izJBeYAmhx/s5M5fZhTWMD36jRJuRj2yle/zg8losqRgFliG0LLto6khbPrsx4/t1SxyPrtyMvGwvnpsSxi9eq01rNgT0ucZh6Ky3KY/Uz7EourQH7lu2ETcPz8NPwv0AqDJ3BMA9Bjm7BeVh3D+2AG2CRHWldT5t1V930M/o18Of5pSoj313Yxt+/349Zt50Ga10PPWX7WnBfvXaXVi3pxmVJcOoVOKciSNwY/Xf09wvv9jXbM+T9rKO6ht3BfAMobx5I2eYd2h9zGTDHQB4bMbvcWj8mZTC41kGotyuaa9zwXmHKnOZ3li4cHG+w03bGXAqHrAV9KBW13M+F1klSZLRGk9CVhS0xpOIJ7TvEBdthf57ZZl7rvWFL7UUp6tkpLok9srygmcZPDs5jJJwPyiKAiignGaeJVCgACBobktQjdeYoSRJtOyI7gK4uKIY3bwciBZkEKibmIB2fbN8vJtp7iQCPEvl3oz8R2NwaBvYellISnu3fsjLWXKTs3wczfjGkhLV3JUVgNXMH2IdyOeZeKSiqoU8Z+IITBrZH/ct24jrqj7A7sa29PLw8lpEExJiSQk/HdkfO58ej+rJRWAZ4LkpYSphFxUkDO4VTJu/cycVUuOTG6v/DllWwLGqg6jdNdGz7Lo2uRV9xWhNnvp9LxaesxFGtQqdFrThq2bHSvuyoli76DlE20jICqU+7Zg9HpUlw7Di8/1IOESqzqQUXkyUsetoK92wMYRg19FWxBy6+LraRup9dbE0w7pw4WaeNeiarKkUjNO10XZqLHbGCql/87EMmmOJtNL72+sP4GQ0iTvG5NsqGozOz03rgk8NHFJVMvY3RcEQgg93HsU1Bb1ACNAj6DGV0qtKi7D54HH695ygSoFpiiaQo5mb5IQ88DAEjNZEJskKfBwD3s0snxWM8yPgYfHidNVw4YVpIyErQLafp655dgopuxoiGJLXHkTublTpNKnKEuOG90FlzTYsKAsjaCih9+vux0sf78G44X0Q8LB4YVqxKUO8oCyMfx4+ST9TL1X/65LPsG5PE/bMuYV+tl0wG/RyuHvpBlRPKUIiKYFlCGauqDNlCBkCFPzybZQU9aWOgfubotQ1U/++ehbaGOynXpP6o5G0/9bHUtA7lGZNninZyq4Ev4fBsL7dTZWluZMK4fc4pfOcWdqGkfqkg2MIHrhhiCPnN/KGAYMUogMmKT6OQb/uAXPFpixMq4Fni46Uely1DRcXA9zgWcP5oslqHcSH0c3LQZAVBL0cFEXB9sMn8bftR3H7mEG0oU8f94PLa/HCtGIISYk2jqSWNgmBSVrvjx/vxe1jBlkGDgePxxDwsFAUBTlBj2pYMrgnGKK5xzEEpaMuxf1jh6A1nkSWj4OHy4GkKHh13T784LLeCOUGEPCw8DCEluIBAJ3kl7uwhx4w+3kGTW3mjdTC8ivRzcsikpRN5ee5kwrx3pcNqCotwiMr24POqtIizH3nS/znT9pl5IwW16n0mkVTR2L1pkO4tfhSqt/s9zBpEmXzy8L4+fUF2N3YhhWf76fcZiDdPdDojmYXzEbiInpleSEkZXiyWUjRJKpKC3FJNz/Vhb5Dk/yqqTuMxlYB86eEwRBCFUiMVI+RA7qje4BHwKvqhX+8qxH/vryW3i9Va3ZgdH4ufvezMGIJGbt/ewu+PqmqxxACeh0q//ef2Lj/BA3WL0ZXQR3Ghjig3Q59cUWxI9KRmaZtZJ6znTnesFEpBDDrPGc5sM4yBPjZdwcgElcrKl6Owc++O8AxTrULF+c73OBZw/miyWoVxK/f14zib+Wkce/u+n4+vJz1uEM+Di3xJHqwjGXjiJdlUFmzDfNKC8GzDCYW94fXguOn6ya3CiIURS2VEkLAMgRJWcGs1+swblgexgxRs8wsQ6AogI9nQQBMGz0QLbEkooIIlhBwLJNmVOJmmc8cxs2WFYd5xvJNWFxRnPYgffzNzagqLYSXJ6a54WHVp9/qTYfoXHhryxEU9ApSbW21+qBanY+avRairGDyqEupbNjzU4vTgqaHND3mcfM/pNk7PYDVebB6oCKIIjVDycv2pm3+dFOc1IB+XmkhHn5dbVZ9fupIKAD2zLmFUoYicRGrNx3E89OKkaV9Dz1wvmVEnzQ93y+fuhmxpASeUTn38YSESEI1g8nL9uKRcUMx8/U604Zk4/4TNFi/WMxQ7PBNqG1Y23MXO3J+P89a6kj7nTK/yqDJS6avPUdUqcAnVm0xbag5N3h2cZHg4l3ZUxC1yXA5bUACqBzlaFKiShMBD4tYQgJDiGUQP3pwT0unsxemFSMp2WdHHl2pNoXtaWzF6ME9aeOI7pI1Z+IIZHk5SLIClmEgKsChE1GTAcnuxlZ8+5Js+LXsGUMI4gkJSVGGh2fx7OQwDjRHIckKZElBUySB+Wt30oAaUANqn6uMkREYN1sdURysytvd/B7ctXS9ae6Mzs+lQW5etpfOhda4SDdGLEMgadTJjx67HrKiQFZAA5ksv/WDO1WPeefT4xGJi2AZgOcYGqyLMvCQIdiXFVDakB4ItyXNWU1dXq56ShjH2wQIopy22czL9qEk3A+/Wr0Vj988lPKcJ1zZz/L+0pUzFpZfiVyOhQzQKs+ah76fFrjpTZiNrcJFS9UwIipIJsUW3UijI+Op04FdP4dTtI2EKCOakEwB4rOTi+BhGXCOZG+JZVXQicbSTGfNBVmxrHguriiG56zP7kKH60h4/sKNZjTosnOpBiQ+ljE140nSqRsuUhv4JEmmr0myjKZogpqO3L10Aw4dj+Olj/ciIog0G2GEXQd/yMd12Ljxxb5m/P79eso7pGL2A3Pg9zAaBYODoDWRMATo1yNANWrveXUD+vcIgEBt7oOWefbyjCrpBxhk4xhKwaieEsaYIb1Myhhu4JwZGDdbOodZR0lRX6yd+QMAwH/8ZDjWbD1CG5MeGTe0Q9OR0fm5+K624QLU5s0XP9qDobPexmNvbEZSkjHztVqsXH8AIZ9Kd6gsGYaSor62Bg26HvPvfhaGogCKoj7kFRAQjf7wh+mj0CvLaxqX3tgHAOH/fBf3vroRWb72wKmkqC9+9aPLAajn5FkWKz7fb2luoc/1S7r5UbVG1Zi2u7+y/TzN3us88lNxsYfkhbBkeuf01y908AxQPDAnbe1xyKDPVve7TTOoOVvICvDw63WmefTw63WOmbD4PCydg3pDYtWaHfA5UO1ktcA8VeeZdUjxJdOZbRcuzne4M10DwxDkBHgsriimzXhBr5p9TW12ygl4EJdk9X2CBIZROV/RhAQ/z6K5LZGW9coJetAUSeAEQ0yau8aM1YMralFVWpiWjegoi3D4RNyymUvnL+uNUUZ+s6oiQmhXut/DQpIV/L9VW5Dfs708r2fFowlJXXS1dXfZP77CO1sbsLA8DD/PmjIZpyP15+LsYayY6I59j7/ZTiswzqO5kwpR39iGmrrDeHTlZjw/zVqGMJaQML8sjKQk4+fLam2Pf+bWQigKcK+hKWnupEIIoojf/SyMSFyi5e5uAR5ZXg5VpYUQkgr+/X/SG5naBAlE49HbNbkC6kNaD9DX7WnC4zcPhSDJpgyhcaz6MUEvh8qabZg7qRCHT8TQ0CJg3PwPUffrH9reX7pVt34f6O+za7bMRKWqqyLRQXbSe4pjOwPWJnPrVICYaS3jqCDROahDV8c528y8z8Oi6k87TM+FqjU7UD0lfLbDBuBK1blw4aYDNciyguZoEn/8eC8OHY/TzPA9r5qtiHVZLerOt3Q9TkSTiMRFNEUStpaubVr5z6i5q0PP9n2xrxmXdPPjmXfanfoqS4ZRvdRURz6WEKzZegRTUuWOrh4AP9cuVfbWliOorNmGhpY4GEJw77KNGDpLzQQdjybgYRn4eRbVU8K4fcwgeFkCaJlBHR6WARSAYxlMGz1Qy655L/rs2rmGsWLy1pYjKqd3ajFmTxiRJuOV6goY9LCW8+qNDQdwIpq0dZbUj+/Xw2/pkCYr7XxI3TY5KkiY+XodIoKER1bWpd0fuxvbqPsgZzPfBVHNKH5nYA4YAlpx6eb3dPhd9WPaBJFK6xkd2ERZsvy8VRsPorJmG5685XIoigIGwELNcfAfe45ZHuN3KywUmc5OZjJzC8CyCqhzkp1AJl0A2wSRBuaDn3wL4+Z/iIYWwbGsfKYz2y5cnO9wUyQadO5oZckwyw7xypJh1Agh6OVMf3/49ToqL2T3wMjyqcfsb4raSmHp/19TdxhvbTmCnU+Px7j5H6Lyx1fg1uL+WDR1JOUOcgzB33ceRdnVA5Dj99C/Nbepsm8MSxD0cqieXITe2T4caI4i6GHBEqQ5+8VECY2tcfzwuY8wY2wBbrtmEHhezcYTmGXjzsSoxUXmkGrUs6shgl/9eSuemxLuBO+43cJbz06t+Hw/NW041fFRQbJ8j5/nTFxq3fFP/xy78xrdB63G9dOR/elDWgHoRqEj+omxKdHPs/ByDMqvGoCckAdfn4yjenIRegS9eHXdPtP9pStnAKqcmN6MuaSiGIsrikFA8NLHe9LGeMe1+Qi5qjEAYKoO6NDnjROcZ2OAqGN0fq5j2U99E5daRXRCh1lHqsulzyFOi07nMzbUOqnDnOnMtgsX5zvcVV6DzmfsTNDQEkum/d3vYfHEqi2n5OHNX7uTZq+MHOU1W49Q8wb9mEhcxOj8XMz+y3Z8tKuRZnlZhsCnue9lezkwmkLCq+v24d//ZxMtfRMAHGte6GUF+HhXI+VbN7QKqD/ail5ZPux8ejxuHzNIldY6h6YvLs4MUUFCZc021NQdTuM/A2be8bzSQmT5VR1bY3Zq4Xv19GF4quNPxhKW77ELZlXpNuv7Q9dO1jenVuPq18NPs4t+D4txw/vglU/3dnjPGc054km1+iNIMoSkjKSkwK9Rr97Z2oDwf74LRQFGzV5LA2d9TAW9Q+iV5cWJWBJ3L90Av4e1HKNrEtGOTGZWAVUNwzL771CjpijD0iTFKZMXn4fF7P/bTnn4gihj9v9tdyRzbtRh1se+etNBxBLODN5IOTFmtnVqlQsXFzrc4FmD/gA+VdCwoCyMdbuPWf593Z4msMSeYgEADS0CEqKMZ24tpA/2vt19mH7NIKzedBBvbTmiHlOuynHp7lyjB/cEp51DkhX892df4e6lG9AcTeLVdftwIprEtNEDsbiiGN29HJrbEvi6JaZKxmmNfEGPmu0ZM6QXdfS7pJsXBb2zaMDsNvd1LehSdXe9sh6zVm/B89NGovbXN6GgdxALUjZp88vCGNwrSAPQjhr71mw9kjaP9eOfuVWVN7ykmy/tPXMnFeLQ8ZjleXc1RBDwsKgqLbJ0/NPfF7EJhltiSVP5ubJmGyYW9wdLCJ6dXJR2z738yV7aqDaif3cA7XJmOq0kIcmmIK+j+//+6wsoPcTufR0FD2fiYNqVwWoOonMmjsCO2eMxZ+IIhLwcWIeC51hSsgxuY0lnAriA12aD5BDnOZPUCoYAE4v7m+h8E4v7O7ZxyfTGyIWL8x1EccjKtKtg1KhRyvr169Nel2QZh47HsXrTwTSDB90QojUugiFAS1xMa8TSXcv+o+QKTBrZH6KsmCgWb248iHe2NtD3NrYKqCotRFJSMCA3gHhCgqSoJihNEQEBDwe/h1Uttj0sGlsF+D0sQl4OsWR7M2MsKaFnyEs1SD0sg4QkI+TlcPB4DD0CPLJ8vJtBPj2c84tlN09TERFE3PWKSpGo/PEVuGVEH1pm1ik4ujZz9bs7aQPd6PxcVJUWQpJhnutac2tEELFu9zHk98pCQe8QInERr3xqbpwNejm8+NEeSvPQ37PnWJuleUXVmh14asJw/PHjve3HCKLJnVJvyG2Opjfdvr31CL2H+vXw4UBzDN0DPLL9PGa+Vov7riugWfN/7DmGSSMvhd/DUmm+ZyeHMfjJt8AxBDufHo9dDeom4c5r8xFNiojEJfTv4U9r+NXv2eemhDF01tsQZQUlRX0tdaZzgh4EPOmUhAw6mJ63czUSF7HraAsG98oySV8O6Z3tCG1DVhRc9kv199Ch/7ZOyL21xtUqQ6qUo2ry4oDcW0LESUFMc4ft5uXgtZhDpwNJktEqiGka1VlezhEzKllWlaSOG87fiWfNOZ2rnV1TT1ce7nzC6UrVuVJ4lujUPHWJqxqiCYlaDvft7lP5jz4eLfEkKmu2oaq0CC0x1WSh/KoBJrtqo93vO1sbUBLuB1ZbQHRDkWmjB+IHl/VG9btq4KwHKQePx9AaS6rmIYRAlhWIkgL9cUCI+r+gj1Mzz4ZGPi9LQAhrkItT+cs+jgHDEPTM8l607mYXMlItuHWKRKpecfXaXVi3pxkvTh9FNY11DvC80kLMW7MD+T2D1DTk0PEYkpIMhiHwsAzCA3pg5mt1NBCffs0gPHDDEMoJHpgboGYmqcF6Y6uAZ24tRN/ufrQJ6ibv2clhCEnJ8pgHbhiC/U1RzP7LdtTUHUblj6+gHOTWuAhRkjD1uwPx3fyemg3wIAiijKWf7sPtYwZZcl/HfjsPwyvfp/82Wmy3xkSqvOHzsHjyT1tw33UFIIQgKamVoX49/FRt560tRzDzpssoh1e/3/V1YFdDx5zP88XB9JuE38Ogd5bfZBFdVVrkmD13xh0APSyqpxTRe+A7A3NQPaXIMWqOpIDa1+ubC4ZRXz9bsCyjBsoMoc8HJ11cGUatUrIsA0LgPmsuErjBdjsuzFX7DBDwsGkZZ2OWeHdjG37/fj0eHTcUOSEP+LgIWVJoVlgPShaWq25pRMt8MASIJSTwrKqrXD0lrBlDELXZK+ShMlhJUYaXZ8GxJI1Poy9JhFEl5hRFQVIGgh6O0i0AIMtAubhQH8oXM1IzmGtn/oAGEHZ6xT4PC3+SpYHeoeMxEADPTg6j/mgEv/nzVjw7OYxrn3mfmqRcku3Dyi8OmBqCXvlEtXDXA/Q1D30fG75qNjXafVLfiGs1t8nH3thsCrwBoFUQEfSwpmMURcHST/dh7Lfz6L20ZlsDxo/oA1lWIIiSKTtXPaUIT/5pK2rqDoNjCO68Nh/PTi7Cwwa3vwXlYaz4bL9ps6BbbM+dVIiglzXZRVsF30sqiuFhCW4fowb38YSEheVhzNDG0tgqgCEED62oRU3dYVVmzEaq7nQcTI2bo65s7x1NtCurAO2No07Zc2c6uI0l5LR7YOUXB3DHmHyEHBi/h2UQSajZ4aBGtese4BFyaPwsy2RUOpRhiNtA7uKihTvjNegNFnrGSS1zq4GzkZZhpFtk+3mEvBxeqChGyKBeEU1KePnjPegW4DFpZH/VmU97+CmKoloFCyJ8PIumSAJygIeXYwBO3cV7ORZ/+GgPLWUvLFdL2TFRBiGqXBwBcaT06aJrITWDWf3uTqp12xJLWmbiWmPt/No2QTTpjAPtWVk9sNQtq40ZYqpYwbV38Rf0DuFHCz+yLJu/9PFeVJYMw5C8EBpOxhGJJxHycjgRTWLjV80YPbgnAOBENEnpJBv3nzBlcl/7fD/uGJOPpCib7ss5b31JM7/fGZgDn4fFM3/aYgpy3t5yBHeMyccDNwxBa1xEQpToZkGvMAHtAWxVaREeWdkehD07uQizVm9FQ4vqFhj0qI52Pp6lyibGrLRuqmTnKthZB9MM0ju+cWRaqi6akCyD29vHDHIkONd5w+kOgA4MHgDHMQjBnB32u06sLlx0CXT56IsQcjOABQBYAH9QFOW/zuQ8xoUyL9uLh268jGaJjQ9Inf/cJkj4cOdRvPD3vZhXWohfaw/aBWVhdPdxuH3MIAS9HBJJyUTBUGRQG259wfQwRC3hGVQu7rhWffAbM0+6BJa7y794kZrBrKk7DIYASypGwcczltJaoixhhqY9Xv/0+LRAcUFZGLkhD+ZMHEE3iTV1h5GX7TXJGn68qxHD+3WnXfwxu4BQkLDwvXpUr92F3b+9Bdc+835agL1j9nh8uOMorujXjWabG1sFcCzBzNdq0dCiblqf/NMWmtVddudVYIiZfjJ3UiGiNpJlP72yP2RJgaBpr6dWlPTxxhIy5r7zJQ329zdF8V9vtwfoRnpFarbN6j61/N00Pe7UoDg12L6Q6B2Zlqrz86z1Bs8htQ3G0PCo83pDXs7RpjiOY2i10DUXceGi66BrrcYpIISwAH4P4CYABwF8QQipURTlnx0faY1Uzc3WWBJejqFl24aTcapYAQDfv6w3ir+VA5YQVE8Jo00Q0dgah8/DUnWNhKQglpQQ8HBoiiTQI8CDZxnwBk40z7HwGlZktxzmwg5WGcyGFgEgqvpAKo1i9aZDmDZ6IA24dze2pTlS6vrEqRSk4m/l4M0NB3HTFXkI+TiMHtwTWT4OZVcPwIPLa5GX7U1zeFtQHgZDcEonvvqjEdz28nq8fNsok6Mlo91LqZvWeaWFtC8h1U3zzmvz08dRpqrVtCUlHDoRpZ/RGlcbFI3nBQGtKv33XVfjxuq/m4J9O3rF6dynqXrcdsH26dA7znfoigyZytxazfd1u49hzJBeCyutaQAADqJJREFUlK5wNvBwLERZQfcAD0KA7gEeHEPg4breb+HChQtn0dUjs6sA1CuKsgcACCErAPwEwGkHzxwBOIYB0C5zpAAqVQIq3SLk47QGPoLmtgR+/Wc12zyvtBBVf9qhlXjD4AihckwcY84ypzZtuMGxi9NBRxlMRVFQ/K0c3LdsI7XnXrOtAaMH9zRZeFupRLy54QAmXNnP1KTHEmDNtgbUHjiBWf9yOSJxCVk+HooCGozGEhJtONSVZY5F4pSDvOiDesvAdsXnKh/5hQ/34rkp3ei9tKA8DAIgIUkoCffD/WOHUPMIWVYsy+gA0D3goWPSg6jL+3TD33cexfgRfXDPqxtw8/A8/CTcz3TekJfDmxsO0EDargnNCdvtzgTbnaV3dAVwNplbzimdZ46l8z2VWuQEGIYg4OEQ1aTvOJbpsvxzFxcHurJSSFdDl5aqI4TcCuBmRVHu1P49DcDViqI8kPK+uwHcDQADBgwo/uqrr9LOJYoyZFmGICvt7ns8i1hSgpch2NUYwf7mKMYM6UUzR/r7WELg87CU8+xy1ro8zsnTsTPzFOi4oUySZEQ1KcN4QoKsqEYgTW0J2nSnN/CFvBya2wQEPRx8HtYkl9gmiPAyhN4Pxr9FtQyxz8NCTEqme4YlBF7tvmmNJdE724e2hAgCmM4bFWVk+/m0+8fLEDBMeyPVpTkBHG2JI9vPw8cxafJbPQK82mwVTZiaCheWh+n3SiQlJLUxGv+7TRBVSUkfT88V8nJojibPGef4DDjP5+1cFUUZkiwjYbjeHoaAZRjH1khRlBETJZNjqrv+nrf4xudqZ9dUI9wA9NzhPFHn6NQ8vSiCZyM60npMXYj14MTLEHB81+58d3FaOOc/cGc1STsLU8BtCH7bBNFWwup0VR+M748nJciyajTRUYBv9/mp96KHIeB5lm4IAl7OdN4zUaiwO+Zcq12c5uef13PVDW5dGODqPLvoEF0peO5adcB0HAJwqeHf/bXXzghWzRvGru2uVjZ14UKHiTJgaEzqqEnpdLn3xvcbjUJSj+2MhJZdI1XAa33eM+kTsDvmXPccnOvPdxJuQ5wLFy4uRHT1FMAXAIYQQgYRQjwAygDUnOMxuXDhwoULFy5cuLhA0aXTGoqiiISQBwCsgSpV95KiKNvO8bBcuHDhwoULFy5cXKDo0sEzACiK8haAt871OFy4cOHChQsXLlxc+OjqtA0XLly4cOHChYv/3969x8pRlnEc//6gFLSFXigh0BZblIuVGCgNKSkpBQz3WFFMELSgGINECjFeSkgM/CGCEtQGI9GCiBTBlou1BKFy1UqBcuuVQilHKIKlciuoBe3jH/Oednt69pyZbc/Ozp7fJ5ns3OeZd595593Z2R2zpqn8lWczMzMzq7a+/qeTHflvHpX+q7pGSHod6P3PHrc1Ali/g8Mpk/envvURceIOWldDtiNPi2i3HCiiXfa9Krla9fKucvytEnupuZojT1ulnLpyXMVsb1y58rTfNZ4bJWlxREwoO44dxftj/bnM+vO+l6Hq5V3l+KscezO1ajk5rmKaFZfveTYzMzMzy8mNZzMzMzOznNx4zu8XZQewg3l/rD+XWX/e9zJUvbyrHH+VY2+mVi0nx1VMU+LyPc9mZmZmZjn5yrOZmZmZWU5uPHchabSkByStkLRc0oVp/HBJCyQ9n16HlR1rEZJ2lvSUpPlpeKykRyWtlnSrpIFlx5iXpKGS5kp6VtJKSUdW/f3pa+2a13m1U/5XjaQTJa1KZT2j7HjyqnfMVE3X3LetNSM/i9a/ysxMMS2RNL5mXWen+Z+XdHbN+MMlLU3LzJSknLHlqhsl7ZqGV6fpY2rWcXEav0rSCTXjGy7bIuf5ZpbXZhHhrqYD9gHGp/7dgeeAccAPgRlp/AzgyrJjLbhf3wRuBuan4d8BZ6T+a4Gvlx1jgX35NfDV1D8QGFr196cJZdaWeV1g/9sm/6vUATsDLwD7p2P1GWBc2XHljL3bY6bsuBrYj61y391WZdOU/Cxa/wInA3cDAiYCj6bxw4E16XVY6h+Wpj2W5lVa9qRG8qNe3QicD1yb+s8Abk3941K57QqMTeW58/aWbZHzfDPLq7PzlecuIuLViHgy9W8AVgIjgalkbybp9TPlRFicpFHAKcCsNCzgWGBumqUy+yNpCDAZuA4gIt6PiLeo8PvTDO2Y13m1U/5X0BHA6ohYExHvA7eQ5VzL6+GYqYyuuW/baEp+NlD/TgVujMwiYKikfYATgAUR8UZEvAksAE5M0/aIiEWRtQxvJEedVrBurI11LnBcmn8qcEtEbIyIF4HVZOXacNk2cJ5vSnnVcuO5B+lricOAR4G9I+LVNOk1YO+SwmrET4DvAJvS8J7AWxHx3zS8luqcFMYCrwO/Sl81zZI0iGq/P03VRnmdVzvlf9WMBF6uGa5kWXc5Zqqka+7b1pqenznr33px9TR+bTfje1Okbty87TT97TR/0VjzKHqeb1Z5bebGcx2SBgO3ARdFxDu109InlUr8TYmkU4F1EfFE2bHsIAOA8cDPI+Iw4D2yr282q9L702ztktd5tWH+W5P1dMy0Mud+62ml+rfF86Plz/NuPHdD0i5kCT47Im5Po/+RLvWTXteVFV9Bk4BPS+og+9rkWOCnZF9rDEjzjAJeKSe8wtYCayOi8wrQXLKDrKrvT9O0WV7n1W75XzWvAKNrhitV1nWOmarYJvcl3VRuSC2naflZsP6tF1dP40d1M74nRevGzdtO04cA/2wg1jyKnuebUV5bceO5i3QPz3XAyoi4umbSPKDzl5pnA79vdmyNiIiLI2JURIwhu8n//og4C3gAOD3NVqX9eQ14WdJBadRxwAoq+v40S7vldV7tlv8V9DhwQPoF/0Cy92BeyTHl0sMxUwl1cv+LJYfVapqSnw3Uv/OAaelfJCYCb6fbFe4Bjpc0LP3TxPHAPWnaO5Impm1No5c6rYG6sTbW09P8kcafkf6NYyxwANmP8Rou2wbO831eXt0F6W7rX3geRfZVwBLg6dSdTHZvz33A88CfgOFlx9rAvk1hyy9q9ydL8NXAHGDXsuMrsB+HAovTe3Qn2a9oK//+9HGZtW1eFyiDtsj/qnUpz54j++X9JWXHUyDubo+ZsuNqcF825767bcqmz/OzaP1L9g8QP0sxLQUm1KzrK6neWg18uWb8BGBZWuYa0kPwiuZHvboR2C0Nr07T969Z/pK03VXU/GvF9pRtkfN8s8srIvyEQTMzMzOzvHzbhpmZmZlZTm48m5mZmZnl5MazmZmZmVlObjybmZmZmeXkxrOZmZmZWU5uPJuZmXUh6QZJp3czfl9Jc1P/FEnz6yzfIWlEX8dpVi9Xre+48WxmfUrSGEnLGlx2c0OlzvQJkmb2so6hks5vZPtmXUXE3yOioYZKeoiDz7vWMpyTjXGB9QOS7pT0hKTlkr6Wxp0r6TlJj0n6paRr0vi9JN0m6fHUTSo3euvPemuoRMTiiJjey2qGAm48W48kTZO0RNIzkn6TRk+W9FdJazqv7NX7MChpT0n3pnp2FtmDGzrnXyXpRrKHMoyWdLykRyQ9KWmOpMFp3g5Jl6XxSyUd3Jy9tyopkKuDJd1Xk09T0/jucrJQm0DS0ZKeTt1TknYvoSjKU/bTfdz1fceWp/B8iOxAGQl0AMOBXYA/A9ekeW4Gjkr9+5E9TrT0fXBX3Q4YAzwLzAZWAnOBD6cc/AHZ07YWA+PJHqf6AnBezbLLelj3FLY8GetS4HrgQWANMD2NvwX4d9rOj8ouD3et1wGfIHsS2og0PBy4geyJajsB44DVadrmnOySfzOB76X+U8ieKDcizb8JmJimjQAeBgal4e/WLNcBXJD6zwdmlV027lqrK5irA4A9Uv8IsqfsqZuc3LdomwD4AzAp9Q8GBpRdNs3sBmD9wXRJp6X+0cCXgIci4g0ASXOAA9P0TwHjsse9A7CHpMER8W4zA7a2cxBwbkQslHQ9W64EvxQRh0r6MdkJYBLZY2CXAdc2sJ2DgWOA3YFVkn4OzAAOiYhDt3MfrH0dC8yJiPUAEfFGqgPvjIhNwApJe/eyjsnAZ9Pyd0l6s2ba3yJiUeqfSNbAWZi2MRB4pGbe29PrE53rM6tRJFcFXC5pMlljeSTQOa02J4+gYJsAWAhcLWk2cHtErO2b3W1Nbjy3OUlTyJL/yIj4l6QHya4CfrzOIjuRfRr9T3MitH7i5YhYmPpvAjpvtZiXXpcCgyNiA7BB0kZJQxvYzl0RsRHYKGkdW04UZo3YWNOvunP17r0u61kQEV/oZZv/w+doy6+7XD0L2As4PCI+kNRBdnECts7JntRrE1wh6S7gZLIPgidExLONhV49vue5/Q0B3kwN54PJrnoMAo6WNEzSAOBzNfPfC1zQOSDJV+tsR4g6w50V/ia2rvw30VjDoXYdbnxYXvcDn5e0J4Ck4Q2s42HgzLT8ScCwOvMtAiZJ+liad5CkA+vMa9ZVkVwdAqxLDedjgI/Ume9xCrYJJH00IpZGxJVp+X51f74bz+3vj8AASSuBK8gq7leAy4HHyL566QDeTvNPByakHyOsAM5resTWjvaTdGTqPxP4SxO3vYHsNg6zbkXEcuD7wEOSngGubmA1l5H9aGs52e0WL9XZ1uvAOcBvJS0hu2WjXzU8rHEFc3U22fl8KTCN7Fvn7tbZSJvgIknLUg5/ANy9XTtWMUo3e1s/03kfc/qUeQdwfUTcUXZc1n4kjSH7ELcYOBxYQXbf/QpgQkSsl3RO6v9GWqYDmED2Q5T5EXFInXVPAb4VEadKuhR4NyKuStOWAadGRIekm4FPAndHxLf7Zk/NzKrJbYJi3HjupyRdRXYv9G5kX8tcGE4GMzOzfsdtgmLceDYzMzMzy8k/pjGzlifpBODKLqNfjIjTupvfzMysr/jKs5mZmZlZTv63DTMzMzOznNx4NjMzMzPLyY1nMzMzM7Oc3Hg2MzMzM8vJjWczMzMzs5z+D5MZCGzAeA5vAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<Figure size 720x720 with 20 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#两两变量分析\n",
    "print('两两变量分析：')\n",
    "variables = ['sex','smoker','region','age','bmi_int','children','charges']\n",
    "sns_plot = sns.pairplot(df[variables])\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "_cell_guid": "bdf90848-3c21-4d3c-91be-2e30ecc6d7d8",
    "_uuid": "f97e66a90b2bb51c02190aa3620ed716b86a343d"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "建模与评估\n",
      "\n",
      "\n",
      "RandomForestRegressor evaluating result:\n",
      "Train MAE:  1098.820067004157\n",
      "Train RMSE:  1966.5403592957734\n",
      "Test MAE:  2314.1670691321488\n",
      "Test RMSE:  4230.449393914039\n"
     ]
    }
   ],
   "source": [
    "print('建模与评估\\n\\n')\n",
    "\n",
    "#对类别型变量进行编码\n",
    "le_sex = LabelEncoder()\n",
    "le_smoker = LabelEncoder()\n",
    "le_region = LabelEncoder()\n",
    "\n",
    "df['sex'] = le_sex.fit_transform(df['sex'])\n",
    "df['smoker'] = le_smoker.fit_transform(df['smoker'])\n",
    "df['region'] = le_region.fit_transform(df['region'])\n",
    "\n",
    "variables = ['sex','smoker','region','age','bmi','children']\n",
    "\n",
    "X = df[variables]\n",
    "sc = StandardScaler()\n",
    "X = sc.fit_transform(X) \n",
    "Y = df['charges']\n",
    "X_train, X_test, y_train, y_test = train_test_split(X, Y, test_size=0.2)\n",
    "\n",
    "#训练集模型\n",
    "regressor = RandomForestRegressor(n_estimators = 200)\n",
    "regressor.fit(X_train,y_train)\n",
    "\n",
    "#prediction and evaluation\n",
    "y_train_pred = regressor.predict(X_train)\n",
    "y_test_pred = regressor.predict(X_test)\n",
    "\n",
    "print('RandomForestRegressor evaluating result:')\n",
    "print(\"Train MAE: \", sklearn.metrics.mean_absolute_error(y_train, y_train_pred))\n",
    "print(\"Train RMSE: \", np.sqrt(sklearn.metrics.mean_squared_error(y_train, y_train_pred)))\n",
    "print(\"Test MAE: \", sklearn.metrics.mean_absolute_error(y_test, y_test_pred))\n",
    "print(\"Test RMSE: \", np.sqrt(sklearn.metrics.mean_squared_error(y_test, y_test_pred)))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "_cell_guid": "0d024932-ba9e-47aa-9e92-893b37d5c420",
    "_uuid": "9e7392173889c190c75d1d87ff1ee672cda9aa12"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "特征重要度排序\n",
      "\n",
      "\n",
      "1.smoker(0.635514)\n",
      "2.bmi(0.200186)\n",
      "3.age(0.125209)\n",
      "4.children(0.018970)\n",
      "5.region(0.014224)\n",
      "6.sex(0.005897)\n"
     ]
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "print('特征重要度排序\\n\\n')\n",
    "importances = regressor.feature_importances_\n",
    "std = np.std([tree.feature_importances_ for tree in regressor.estimators_],axis=0)\n",
    "indices = np.argsort(importances)[::-1]\n",
    "\n",
    "importance_list = []\n",
    "for f in range(X.shape[1]):\n",
    "    variable = variables[indices[f]]\n",
    "    importance_list.append(variable)\n",
    "    print(\"%d.%s(%f)\" % (f + 1, variable, importances[indices[f]]))\n",
    "\n",
    "# Plot the feature importances of the forest\n",
    "plt.figure()\n",
    "plt.title(\"特征重要度\")\n",
    "plt.bar(importance_list, importances[indices],\n",
    "       color=\"r\", yerr=std[indices], align=\"center\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "_cell_guid": "35dcf7ff-9e8d-4090-b4ca-8910d610fc3a",
    "_uuid": "834b9c0f72d55e8db00fdf7c6e611cc87557fbb9"
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "在新数据上进行预测\n",
      "\n",
      "\n",
      "Billy -  ['male', 'yes', 'southeast', 25, 30.5, 2]\n",
      "Billy的医疗开销 =  34408.38707224999 \n",
      "\n",
      "\n",
      "Dennis -  ['female', 'no', 'southeast', 45, 19, 0]\n",
      "Dennis的医疗开销 =  8746.031562649998\n"
     ]
    }
   ],
   "source": [
    "print('在新数据上进行预测\\n\\n')\n",
    "\n",
    "billy = ['male','yes','southeast',25,30.5,2]\n",
    "print('Billy - ',str(billy))\n",
    "\n",
    "billy[0] = le_sex.transform([billy[0]])[0] \n",
    "billy[1] = le_smoker.transform([billy[1]])[0] \n",
    "billy[2] = le_region.transform([billy[2]])[0] \n",
    "\n",
    "X = sc.transform([billy])\n",
    "\n",
    "cost_for_billy = regressor.predict(X)[0]\n",
    "print('Billy的医疗开销 = ',cost_for_billy,'\\n\\n')\n",
    "\n",
    "\n",
    "dennis = ['female','no','southeast',45,19,0]\n",
    "print('Dennis - ',str(dennis))\n",
    "\n",
    "dennis[0] = le_sex.transform([dennis[0]])[0] \n",
    "dennis[1] = le_smoker.transform([dennis[1]])[0] \n",
    "dennis[2] = le_region.transform([dennis[2]])[0] \n",
    "\n",
    "X = sc.transform([dennis])\n",
    "\n",
    "cost_for_dennis = regressor.predict(X)[0]\n",
    "\n",
    "print('Dennis的医疗开销 = ',cost_for_dennis)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
